In response to the need for greater cohesion among regional conferences, the Asia Pacific Bioinformatics Network (APBioNET) set out in 2015 to realize a long-held aspiration-a single, unifying bioinformatics "super conference" for the Asia & Pacific community. Nearly a decade of persistence, coordination, and coalition-building led to the inaugural Asia & Pacific Bioinformatics Joint Congress (APBJC2024) in Okinawa, Japan. Now established as a triennial event, APBJC stands as a testament to the power of collective vision and shared purpose, offering a unifying platform for regional collaboration and scientific exchange. Tagline: Bringing a Region Together: The Making of APBJC.

The Outstanding Contributions to ISCB Award recognizes an ISCB member annually for notable service contributions toward the betterment of ISCB through exemplary leadership, education, and service. The 2023 Outstanding Contributions to ISCB Award recipient is Shoba Ranganathan. She will be recognized with this award at the 2023 ISMB/ECCB conference in Lyon, France. Prof. Shoba Ranganathan, FABACBS, Macquarie University. Shoba Ranganathan is a Professor of Bioinformatics at Macquarie University in Sydney, Australia. Ranganathan’s research interests include immunoinformatics, transcriptomics, and biodiversity informatics. She is a long-standing ISCB member and has served the greater bioinformatics community for over 20 years. Ranganathan was born and raised in India and received her PhD from the Indian Institute of Technology in Delhi. Her bioinformatics career has spanned the globe through academic and industry positions in India, France, the USA, Singapore, and Australia, which has given her a unique and valuable insight into bioinformatics research and education activities in diverse settings. Shoba first became a member of ISCB in 1999 when she had a paper accepted at the Pacific Symposium of Biocomputing (PSB). It was there she met some of the pioneers of computational biology, including Russ Altman, Larry Hunter, Subramanian Subbiah, and Keith Dunker, among others. This led to her getting involved with the Asia-Pacific Bioinformatics Network (APBioNet), which was the first regional affiliate of ISCB. Shoba has held numerous leadership roles in APBioNet, including Vice-President (2000–4), President (2005–16), Advisory Board (since 2020), and Board of Directors (honorary) (2016–present). She has also built ISCB’s connections with other international scientific networks, including serving as a founding co-chair of CompMS [joint initiative of ISCB community of special interest (COSI), Human Proteome Organization, and the Metabolomics Society]. Shoba is a founding president (2003–5) of the Association for Medical and Bio Informatics Singapore (AMBIS), ISCB regional affiliate, and a founding member of GOBLET (Global Organization for Bioinformatics Learning, Education and Training) (2012–present) and hosted their annual meeting at the International Conference of Bioinformatics (InCoB) 2019. She has also been instrumental in facilitating the peer review of InCoB papers in BMC Bioinformatics (2006–present), followed by the addition of BMC Genomics, BMC Medical Genomics, BMC Systems Biology, and BMC Cell and Molecular Biology. Ranganathan has directly served ISCB in various roles, including as a member of the ISCB Board of Directors (2002–6), on the Education Committee as Co-Chair (2003–4), Chair (2004–5), and current member, and as a Co-Chair of Affiliates Committee (2004–6). She campaigned for parallel sessions at ISMB, which was adopted from 2004, switching from the single session program until 2003. Her service has been pivotal to realizing ISCB’s role in promoting bioinformatics education. She recalled, “I moved to Singapore in August 2000, where I put forward a proposal for a Workshop on Education in Bioinformatics (WEB) for ISMB2001, organized by Søren Brunak. I kissed my bank account away signing a personal guarantee for the entire cost of this Special Interest Group meeting. It is gratifying to note that WEB is still on the agenda (as a COSI now), and fortunately, all SIG meetings are underwritten by the ISCB nowadays.” Shoba’s service has been driven by a desire to better connect the global bioinformatics community. She still sees a “digital divide” among the bioinformatics communities in the Asia-Pacific, especially in under-resourced areas. Ranganathan has worked to connect these groups through activities with APBioNet, Bioinformatics Australia/ABACBS, ICSB, and other societies, which has been critical to improving bioinformatics education and supporting newly formed bioinformatics societies. Her work in this area has been pivotal in building bioinformatics education and infrastructure in Australia. Her work has been recognized with multiple awards, including the 2018 ABACBS Honorary Senior Fellowship, and as the first UNESCO Chair of Biodiversity Informatics in 2006. Shoba remains deeply involved with the bioinformatics community, especially as she anticipates the global reach of bioinformatics to expand to applications including environmental and health research, synthetic biology and gene modifications, and artificial intelligence for biological knowledge integration and analysis. She is honored and grateful for her recognition with the 2023 Outstanding Contributions to ISCB Award and encourages junior scientists and trainees to seek out varied service opportunities to expand their knowledge and give back to their scientific community.

The ISCB Overton Prize recognizes early or mid-career scientists as emerging leaders in computational biology or bioinformatics who have made significant research, education, and service contributions to the field. In 2001, the Overton Prize was established to honor the untimely loss of G. Christian Overton, a leader in the field of bioinformatics and a founding member of the ISCB Board of Directors. The 2023 Overton Prize winner is Dr. Jingyi Jessica Li, a Professor in the Department of Statistics (primary), Department of Human Genetics and Department of Biomathematics (secondary) at the University of California, Los Angeles (UCLA). She will receive her award and give a keynote talk at the Joint ISMB/ECCB conference in Lyon, France, this July. Jingyi Jessica Li, University of California, Los Angeles Jingyi Jessica Li grew up in Chongqing, China, immersed in mathematics. Both of her parents were math majors and went on to become math teachers. Her mother in particular fostered Li’s mathematical curiosity, as she believed that everyone can learn and grow in mathematical understanding. She said, “My mom thought that math is like exercising. Everyone should do some exercise, even though we are not all top athletes going to the Olympics.” Although Li was exposed to math at a young age, she considered it a mature field and wanted to pursue studies in an area that could feed her curiosity. She entered Tsinghua University in China in 2003 and pursued a degree in biology, which was stoked by her interest in the Human Genome Project. She recalled, “It was a very exciting period with all these new technologies that could discover unknown things. I knew that to analyze this data we would need math, so I thought I should use my skills to approach biological questions. That’s why I decided to learn more statistics.” Li pursued her interests in biology and statistics through her Ph.D. studies at the University of California, Berkeley, under the joint mentorship of Professors Peter J. Bickel and Haiyan Huang. Bickel is a world-renowned theoretical statistician and Huang is a statistician with expertise in bioinformatics. Bickel and Huang collaborated on bioinformatics projects, which offered Li the benefits of observing and learning from different perspectives in tackling research questions. When she joined their teams, they were both involved in the Encyclopedia of DNA Elements (ENCODE), which was developed as follow-up to the Human Genome Project to identify functional elements of the human genome. These studies generated enormous amounts of data due to the emergence of next-generation sequencing (NGS), leading to technologies including ChIP-seq [combining chromatin immunoprecipitation (ChIP) with NGS] and RNA-seq (using NGS to reveal the presence and quantity of RNAs). Li was interested in how to convert this type of raw data into numbers. She said, “We had not encountered this kind of data in statistics. How do we formulate this information into statistical questions? Sequence data are not numbers, so that forces the question to be important. It was very fun but challenging because we had to gain consensus on how to analyze those data. Everything was open and new.” She also recalled that statistics was a more rigid field set in dogma and theorems. Bioinformatics was more open and flexible, and she could use different approaches, such as computer algorithms or statistical models, so long as a biologically interesting question was being addressed. Li’s fruitful Ph.D. research honed her skills to identify important bioinformatics problems and provide rigorous statistical solutions. Her work was published in high-profile journals and resulted in a faculty position in 2013 in the Department of Statistics, with a joint affiliation in the Department of Human Genetics, at UCLA. She was embraced by her new colleagues who mentored her through her first grant proposals, which yielded funding of an NIH RO1 grant on her first attempt. She was also the recipient of an NSF CAREER Award and Sloan Research Fellowship, serving as further recognition of her research contributions and potential as an independent investigator. Li attributes the early success of her young lab to her first graduate student, Wei Vivian Li, who is currently an Assistant Professor in the Department of Statistics at the University of California, Riverside. She considered working with (Vivian) Li like a mutual learning process as she was a new PI with a new Ph.D. student. They worked together through the early stages of establishing a research program, including gaining funding, and publishing papers. The success of this relationship set a very high benchmark for future graduate students in Li’s lab and helped Li grow as a mentor. She considers the most critical elements of successful mentorship to be transparency, open communication, finding a suitable project for a trainee, and pairing up students to encourage collaboration and mutual support. Li’s intellectual curiosity has brought about her interest in improving the statistical rigor of genomic data analysis. She has had a long-standing interest in this area, and as a PI, she has more experience in developing more rigorous and computationally efficient and transparent solutions. One area where she has improved rigor is the control of false discovery rates (FDRs) in the differential expression (DE) analysis using RNA-seq data, in which a gene’s expression levels measured by RNA-seq are compared between two conditions, and the genes found as differentially expressed are “discoveries” of potential biological interests. Traditional DE analysis assigns a P-value to every gene by assuming every gene’s expression levels follow a negative binomial distribution under each condition. However, this assumption has not held up well when the RNA-seq samples under each condition are not experimental replicates, leading to invalid P-values and an inflated FDR—a co-discovery Li and her postdoc Dr. Xinzhou Ge made in a collaboration with Dr. Wei Li and his postdoc Dr. Yumei Li at UC Irvine. Li was inspired to look at the DE analysis in a different way after she heard a talk by a renowned Stanford statistician Professor Emmanuel Candes who developed the “knockoff filter” to control for FDRs when performing variable selection. This ultimately led Li and her team to develop the Clipper, which is a P-value-free FDR control method that is generally applicable to high-throughput data (such as NGS data) analysis, including the DE analysis. Li is deeply involved in serving the fields of bioinformatics and statistics in many capacities, including work as a journal reviewer and editor, grant reviewer, and meeting organizer. She has developed both undergraduate and graduate courses featuring the use of statistics in computational biology, and her use of statistics to quantitate the Central Dogma is so widely recognized that it has been incorporated into the undergraduate textbook Molecular Cell Biology. Li is currently a Helen Putman Fellow at the Harvard Radcliffe Institute writing a statistical methods textbook focused on the selection of methods that are seemingly similar but have fundamental differences. She hopes that this book will be a useful tool to genomics researchers as they develop bioinformatics tools. She is also working on a statistical framework to address the evergreen question of whether cells belong to a single continuous trajectory or are discrete types. Li’s publication record is diverse and highly cited, highlighting her strong record of outstanding interdisciplinary research at the nexus of statistics and biology. Her many awards and grants from the NIH, NSF, and other institutions highlight her visionary research, but she is truly grateful for the Overton Prize as it comes from her peers who also work at this unique juncture of science.

The annual ISCB Innovator Award recognizes a scientist who is within two decades of completing her or his graduate degree and has made profound contributions to the field of computational biology or bioinformatics. The 2023 ISCB Innovator Award winner is Dr. Dana Pe’er, Chair and Professor of Computational and Systems Biology at the Sloan Kettering Institute and Howard Hughes Medical Institute Investigator. She will receive her award and deliver a keynote address at the 2023 Joint ISMB/ECCB meeting in Lyon, France this July. Dana Pe’er, Sloan Kettering Institute. Dana Pe’er has cultivated her love of mathematics since her childhood in Israel, recalling lessons from her father that revealed the beauty of mathematical logic (Fogg and Kovats 2014). As a high school student, she had her first hands-on experience in the lab of Idan Segev at the Hebrew University of Jerusalam, where she used mathematical modeling to understand subthreshold oscillations in neurons. This project exposed Pe’er to mathematical applications for biological questions, planting seeds for her future research interests. Although Pe’er had contemplated a degree in neurobiology, her curiosity in genomics and bioinformatics was kindled after listening to a mesmerizing talk by Eric Lander describing the onset of the human genome project. She completed her bachelor’s degree in mathematics and master’s and PhD degrees in computer science at Hebrew University. Pe’er’s PhD research mentor Nir Friedman revealed to her the power of statistical machine learning in interpreting complex biological data. Pe’er also came to appreciate the importance of having a strong foundation in abstract biological concepts through her collaboration with fellow graduate student Aviv Regev. After graduate school, Pe’er pursued her postdoctoral studies in the lab of George Church at Harvard University, where she learned to wrestle with the ambiguities of wet lab biology. Her perspective also shifted from asking, “What type of computation can I do for this data?” and learned to ask instead, “What data do I need to answer a biological question I am passionate about?” (Fogg and Kovats 2014) Pe’er also gained invaluable informal mentorship during her PhD and postdoc from Daphne Koller, who not only instructed her in the importance of good modeling assumptions but also provided critical career advice as she prepared to become an independent researcher. Pe’er launched her own lab in 2006 at Columbia University in the Department of Biological Sciences and Systems Biology. During her postdoc, Pe’er realized the power of single cells and that inter-cell variability can be exploited for regulatory circuit reconstruction. Single cell approaches accelerated as she launched her own lab at Columbia University in part through pioneering research with Garry Nolan, for which she developed critical aspects of the computational foundation for single-cell data analysis. These studies opened the floodgates of data science to immunologists and Pe’er was uniquely positioned to take on these studies at the juncture of computational biology and immunology. Pe’er introduced the single-cell field to large-scale analysis with the conceptual framework in which cell phenotypes are constrained to geometric manifolds corresponding to landscapes of possible cell states. This established a now-dominant paradigm that models cell state transitions in development and disease as continuous processes rather than discrete toggles. By leveraging asynchrony in cell states, she demonstrated that it is possible to infer continuous pseudotime trajectories, which provide dynamics from a single sample and generated fundamental knowledge in numerous development, immunology, cancer, and regenerative medicine studies. Pe’er also developed the neighbor-graph-based representation of the phenotypic manifold that serves as the field standard, and guided her development of widely used methods for identifying cell types, visualizing the manifold, deriving pseudotime trajectories, identifying lineage bifurcations, and quantifying developmental potential. As Pe’er became an established PI, she was more involved in the greater computational biology community, including serving as a founding member of the Human Cell Atlas (HCA) Project. She played pivotal roles in formulating the vision of the HCA and has been a key driver of the computational direction of the HCA, especially through her role as co-chair of the Analysis Working Group within the HCA. In 2016, Pe’er moved her lab to the Sloan Kettering Institute (SKI), where she became Chair of the Computational and Systems Biology Program and Scientific Director of the Alan and Sandra Gerry Metastasis and Tumor Ecosystems Center. In this new home, she said, “My focus on biology completely changed. I was in a new environment with great peers, like Sasha Rudensky and Scott Lowe, who also became my teachers.” Pe’er was also given the responsibility of developing the Single Cell Research Initiative at SKI, which has flourished by harnessing the power of single cell analysis to address fundamental cancer and immune system questions. Pe’er’s own team has published seminal findings in cancer research that revealed the complexity of the tumor immune microenvironment and has nurtured her fascination with cell plasticity. She said, “I want to understand how cells work in tissues. Plasticity helps cells respond to their neighbors, and during development, cells lean on their plasticity to form tissues.” Some of Pe’er’s most recent work has shown how the plasticity of tumor cells allow them to hijack and mimic programs of embryonic organogenesis, which ultimately drives metastasis. Although Pe’er gets excited about tackling biology questions, she still loves being in the trenches of algorithm development and troubleshooting technical problems. She considers questions related to plasticity to be particularly well-suited to computational approaches and said gleefully, “These questions require so much math, and math is my playground.” In 2022, Pe’er was awarded an appointment as an HHMI investigator in recognition of fundamental studies on cellular plasticity and how it shapes many biological processes. This recognition validates the broader impacts of single cell studies and solidifies Pe’er’s role as a leader of the field. Pe’er’s impressive publication record and numerous awards further highlight the many contributions she has made to computational biology, including her recognition with the 2014 ISCB Overton Prize. Pe’er feels deeply honored to be recognized with the 2023 ISCB Innovator Award, particularly because it comes from her computational biology peers. Pe’er’s infectious enthusiasm for current research projects is certain to lead to many new algorithms and insights in the future.

ISCB recognizes the outstanding contributions by a leader in the fields of computational biology and bioinformatics annually with the Accomplishments by a Senior Scientist Award. This award is the highest recognition conferred by ISCB to a scientist who has made notable research, education, and service contributions to the field and to ISCB. Mark Gerstein, Albert L. Williams Professor of Biomedical Informatics, Molecular Biophysics and Biochemistry, Computer Science and Statistics and Data Science at Yale University, New Haven, CT, is the 2023 recipient of the ISCB Accomplishments by a Senior Scientist Award. He will be presented his award and deliver a keynote address at the 2023 ISMB/ECCB conference in Lyon, France. Mark Gerstein, Yale University. Photo credit: Robert Lisak. Mark Gerstein was born in New York City and recalled a childhood where his interests in science and mathematics were nurtured and encouraged. As a young child, he fondly remembers becoming engrossed in a science project constructing a model of the DNA double helix, foreshadowing his future interest in biological macromolecules. Gerstein’s intellectual curiosity led him to double major in physics and the history of science at Harvard College. Although he enjoyed physics and was curious about the nascent field of computer science, Gerstein ultimately wanted to pursue a PhD in a growth area of science. He recalled, “I really wanted to look at the confluence of biological science and computation.” This was at a time when the structures of large macromolecules were just beginning to be resolved using computers. Gerstein was encouraged to pursue these interests at Cambridge University through his conversations with Martin Karplus and Don Wiley at Harvard. Their recommendation connected to his ongoing fascination with Cambridge given its storied place in scientific history, including Watson and Crick’s discovery of the DNA double helix and the development of the theory of computation by Cambridge alumnus Alan Turing. Gerstein was given a Herschel-Smith Scholarship to pursue his PhD at the Chemistry Department and the Medical Research Council (MRC) in Cambridge, during which time he worked with computational chemist Ruth Lynden-Bell and protein biophysicist (and 2015 ISCB Accomplishments by a Senior Scientist Award Winner) Cyrus Chothia. His project involved developing computer simulations of liquids, including water, and their interaction with proteins, which laid the foundation for his future postdoctoral studies. Gerstein also came to appreciate that his time at MRC brought him into contact with many gifted scientists, including future Nobel Prize winners such as Venkatraman Ramakrishnan and Richard Henderson. Gerstein moved on to postdoctoral studies in 1993 under the mentorship of future Nobel laureate Michael Levitt at Stanford University, where he used his newly minted skills in modeling to study macromolecular geometry and simulate water surrounding proteins. Gerstein tapped into his computer hacking passion and brought LINUX to Levitt’s lab. He recalled, “Not only was Levitt a gifted scientist, but he was also a computer hacker.” Levitt’s mentorship helped Gerstein realize that working at the interface of biology and computation was an exciting and viable career path. He also got to know Russ Altman during his post-doc and ultimately attended the first ISMB in 1993. Gerstein said, “I started to see there were a lot of things you could do with these large biological datasets.” Gerstein’s productive postdoc years were critical to launching his career as an independent investigator. He was hired in 1997 as an assistant professor at Yale University. He was one of the first computational biology faculty members hired by a large research university, and he had anticipated building a lab that studied macromolecular modeling. Early projects included simulation and classification of protein motions using a database framework. He was also intrigued by the emerging area of genome sequencing. This led Gerstein to study structural genomics and build up his research program with collaborators at numerous institutions. After receiving tenure, Gerstein became interested in human genome annotation and later became deeply involved with ENCODE and related large-scale projects, such as psychENCODE. These interests evolved into several high-impact publications demonstrating that multi-omics data can be reframed as control networks and can be compared to networks in other contexts—for instance, in social relations. These studies have been critical to identifying regulatory sites in genomes and in finding pseudogenes and improving our understanding of genome evolution. Gerstein and his lab were also involved in the 1000 Genomes Project and applied concepts developed from this work to develop tools for more accurate variant interpretation with respect to risks for cancer or neuropsychiatric diseases. His lab now examines many aspects of data science, including the large-scale integration of genomic and phenotypic data, collected by biosensors and images, and the attendant privacy concerns. Gerstein considers his efforts to develop undergraduate and graduate computational biology programs at Yale to be one of his most lasting contributions to the field. He said, “Computational biology is important, and part of making it a field is education.” He has taught his introductory undergraduate computational biology class since 1998, when it began as a 10-student course called “Genomics and Bioinformatics.” He has made every set of lecture slides available online, toward his mission to educate the world more broadly about computational biology. The course in its current form, called “Biomedical Data Science,” provides students with a range of immersive experiences, including the culminating project in which students analyze a chromosome from the science writer Carl Zimmer’s genome and present their findings to Zimmer in person. Gerstein was also integral to co-founding the Computational Biology Graduate Program at Yale with his colleague Perry Miller over 20 years ago and has watched many of the program’s graduates move into their own faculty positions. Gerstein himself has mentored more than 125 trainees, of which nearly 40 have gone on to start their own labs. Gerstein sees his work as a mentor within and beyond the lab as integral to advancing the field of computational biology. His prestigious publication record reflects the efforts of Gerstein and his trainees, including over 650 publications and 189 000 citations. He is an ISCB and AAAS Fellow and has served on numerous editorial boards, working groups and committees. Gerstein is also a frequent contributor to Op-Ed columns, using his voice to communicate the nuances of data science in various contexts to a wider audience. Gerstein still gets very excited about computational biology and considers the field to hold a unique place among the data sciences. He said, “In the future, computational biology has an important role for how we go forward with data science. Now people are seduced by big data, but computational biology is a bridge between big data, physical modeling, and a mechanistic description of how biology is actually carried out on a molecular scale.” The same cannot be said yet for big data applications in political or social sciences, and computational biology uniquely feeds human curiosity as to how living things work. Gerstein is deeply honored to be recognized with the 2023 ISCB Senior Scientist Accomplishment Award, as it is a recognition of his contributions from his peers, and it serves as further validation that the field of computational biology has matured to stand alone and guide the future of data science.

Each year ISCB recognizes outstanding contributions by a leader in the fields of computational biology and bioinformatics with the Accomplishments by a Senior Scientist Award. This award is the highest honor conferred by ISCB to a scientist who has made significant contributions to research, education, and service to the field and ISCB. Ron Shamir, Professor of Computer Science at Tel Aviv University in Israel, is being recognized as the 2022 recipient of the ISCB Accomplishments by a Senior Scientist Award. He will receive his award and give a keynote address at the 30th Conference on Intelligent Systems for Molecular Biology (ISMB) in Madison, WI being held from July 10-14, 2022. Ron Shamir: Founding Father of Israeli Bioinformatics Ron Shamir grew up in Jerusalem, Israel with broad interests in the humanities, science, and mathematics. Shamir was very close to his grandmother who was a pharmacist and had studied chemistry, although he does not recall discussing science with her, and he actually aspired to be an author in his youth. As a high school student at Gymnasia Rehavia in Jerusalem, Shamir became more interested in mathematics, and he recalled, “I had an inspiring math teacher, who really encouraged me. Math problems were like riddles or puzzle-solving challenges. It was fun, and I found that math comes naturally to me.” Shamir started his BSc in mathematics and physics at Tel Aviv University and then completed his degree at Hebrew University of Jerusalem. He pursued graduate studies in operations research (OR), so he could work on a project that connected math with real-world problems, and enrolled in a PhD program at the University of California-Berkeley (UC Berkeley). Shamir’s PhD research focused on the average case analysis of the Simplex algorithm for linear programming, which fell somewhere between OR and computer science. His PhD advisors at UC Berkeley were Richard (Dick) Karp and Ilan Adler, who he considers pivotal mentors in his career. Shamir said, “Working with them completely transformed my perspective on academic research, and even though I got into grad school with no such intention, I left wishing to try for a career in academia. I have been collaborating with them ever since. Dick has always been an amazing role model to me, and I have learned immensely from him. By sheer coincidence, a few years after my graduation, we both independently got into the emerging field of computational biology and worked on physical mapping algorithms. It was a great pleasure working together in this new field. Dick Karp is one of the giants of theoretical computer science, and his championing and involvement in the young field of computational biology gave it great credibility and helped establish the new area as a bona fide scientific discipline.” Shamir went on to his first position as a lecturer at Tel Aviv University in the Department of Computer Science where he worked on graph algorithms and optimization. He spent his first sabbatical at Rutgers University, where he worked on temporal reasoning, which is a problem in which event intervals placed along a timeline are subject to various constraints. Gene Lawler had listened to Shamir give a talk about his work, and he recalled, “[Lawler] told me, ‘This is a great model for physical mapping of DNA,’ by replacing time intervals with clones and the timeline with the chromosome. This encounter changed my life. I started reading about DNA and the genome and was hooked. My wife Michal is a biochemist, so I could ask her all the trivial questions about biology, DNA, etc. It was 1990 and the early beginnings of the Human Genome Project, and there was a lot of excitement about the prospects of combining computation and genomics. I dove into this new area, which did not even have a name then, and was not disappointed.” Shamir has gone on to pioneer various algorithmic techniques in genomics, including analysis of microarray data, regulatory motifs, genome rearrangements, and network biology. Among Shamir’s contributions, he developed elegant algorithms for the analysis of regulatory motifs and protein-protein interactions. Previous approaches have dissected network and similarity data separately, but Shamir and his group developed approaches to analyze these types of data jointly. This led to the discovery of functional modules through the identification of connected networks in the interaction data that exhibited high internal similarity. Shamir continues to be fascinated with topics related to modularity, and he said, “I find myself coming back to the fundamental problem of cluster discovery again and again over the years, and more recently in module discovery based on a combination of similarity and network-based data. This area of study is 100 years old, or 2400 years old, if you start from Aristotle, and is still a lively research area. In a very different direction, I am doing more research on digital medicine in recent years, working on electronic medical records in collaboration with clinicians. This is a tough field. Unlike genomics, where all data is open and well organized, medical data is much more difficult to work with in terms of both data access and data organization. Moreover, physicians are extremely busy work partners and are primarily concerned about treating patients. For them, science only comes second, which makes collaborations more challenging. Nonetheless, this type of research offers a chance to influence disease trajectories and even save lives, so I continue to work in this field.” Most recently, Shamir worked with three of his students and with physicians to analyze COVID-19 inpatient data. They developed a machine learning model for predicting the deterioration of patients 7-30 hours before this process starts and have obtained some promising results. They continue to validate this model by analyzing larger and more diverse datasets, which now include nearly 10,000 patients. Shamir is well known for making his bioinformatics tools, like the Expander expression analysis suite, readily available to the research community as user-friendly software tools. Some of these tools have been written for a specific project with no intention to be broadly useful, but have become unexpectedly popular, such as the simple UNIX program HYDEN he developed with his student Chaim Linhart to design degenerate primers, which is still downloaded hundreds of times per year. He is a pioneer of bioinformatics education and has been posting bioinformatics lecture notes online since 1997, making his course notes some of the of the most widely used and influential bioinformatics educational materials to date. Shamir has been a deeply committed mentor and advisor throughout his career and encourages his students to choose their own projects, through which he advises and guides their research. He also makes his students draft their own research papers and considers the interaction and joint revision process, which includes corrections and rewrites, to be a key part of their education. Throughout the pandemic, Shamir has been constantly adjusting how his lab interacts, be it through virtual meetings or in-person encounters, and he has tried hard to hold face-to-face meetings with his team as much as possible, in order to help keep their training and development moving forward. Shamir added: “I have been extremely lucky in having incredibly talented, creative and driven students. The interaction with them, and later observing their development into great independent scientists and industry leaders, is extremely gratifying. This is the part of my career I am proudest of.” Shamir’s research and leadership have been critical to establishing a globally respected Israeli bioinformatics program. He has published over 300 papers, including five with more than 1,000 citations. Shamir established the joint Life Sciences/Computer Science bioinformatics BSc program and founded the Edmond J. Safra Center for Bioinformatics at Tel Aviv University. He was named the Sackler Chair in Bioinformatics in 2003, and his work and service have been recognized by numerous awards, including the Landau National Prize in the Sciences (2010), RECOMB Test of Time Awards (2011 and 2016), Kadar Family Prize for outstanding research, Tel Aviv University (2017), and election as an ACM Fellow by the Association for Computing Machinery (2012) and an ISCB Fellow by the International Society for Computational Biology (2012). As the 2022 recipient of the ISCB Accomplishments by a Senior Scientist Award, Shamir is deeply honored by this recognition bestowed upon him by his peers, and only wishes his parents were alive to share in this award. He recounted, “As a young faculty member in computer science, I entered an exciting research adventure in an embryonic field that did not even have a name yet. In retrospect, this was a very risky choice before tenure. Seeing how the field developed and matured and being able to help shape it have been great pleasures. This award sums up the path I have taken as a scientist in the past thirty years. I am truly indebted to the society and to the community for it.”

The ISCB Overton recognizes the research, education, and service accomplishments of early or mid-career scientists who are emerging leaders in computational biology and bioinformatics. The Overton Prize was established in 2001 to honor the untimely loss of G. Christian Overton, a leading bioinformatics researcher and a founding member of the ISCB Board of Directors. The 2022 Overton Prize winner is Dr. Po-Ru Loh, Assistant Professor in the Division of Genetics and Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, and Associate Member of the Broad Institute of MIT and Harvard. He will receive his award and give a keynote address at the 30th Conference on Intelligent Systems for Molecular Biology (ISMB) in Madison, WI being held from July 10-14, 2022. Po-Ru Loh: From Math Olympiad to Millions of Genomes Po-Ru Loh grew up in Madison, WI and was encouraged to study arithmetic and algebra from a young age. He recalls liking mathematics in school because of his familiarity with the subject matter, and he also developed an interest in solving mathematical puzzles and competing with his older brother to solve riddles in Brian Bolt’s Mathematical Funfair book. As a middle and high school student, Loh’s interest in math was further stoked by math competitions, including MathCounts and the Math Olympiad, and he went on to be a 2002 and 2003 Gold medalist, and top scorer on US team in the International Mathematical Olympiad. However, Loh’s early encounters with science were somewhat discouraging, as he recalled: “My first experiences with science involved growing lima beans and mealworms. My beans didn’t sprout, and my mealworms died. It wasn’t until high school that I realized that science had a quantitative side, and I became more interested.” Loh received a B.S. in mathematics from the California Institute of Technology in 2007, during which time he was a second-place finisher in both the Google Code Jam and the TopCoder Open. He strongly considered being a pure mathematician as an undergraduate but eventually realized he wanted to work on problems with more direct real-world relevance. Loh ended up pursuing a Ph.D. in applied mathematics at MIT and considers his entry into computational biology to be somewhat accidental. He said, “I had no idea what field of study to pursue, so upon matriculating, I simply browsed through faculty research interests and spent my first year sampling an eclectic mix of courses in different fields that sounded interesting. Computational biology was one of them, and it caught my eye as a growing field with interesting algorithmic challenges.” Loh joined Bonnie Berger’s lab and went on to develop a dissertation project focused on compressive genomics. He worked on algorithms that computed directly on compressed genomic data, which allowed for analyses to keep pace with data generation. In 2013, Loh began his postdoc under the mentorship of Alkes Price at Harvard T.H. Chan School of Public Health and dove further into computational genetics. With Price, he pioneered ultra-efficient algorithms facilitating biobank-scale genomics through the development of two widely used computational genetics tools, BOLT-LMM and Eagle2. These tools have been used to analyze millions of genomes and have brought to light numerous loci that shape human health and disease. Loh became an Assistant Professor in the Division of Genetics and Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, and Associate Member of the Broad Institute of MIT and Harvard in 2018. During his time as a postdoc and a tenure-track faculty member, Loh has had some unexpected findings that have impacted his research. He said, “The most surprising findings in my research thus far have been unexpectedly strong associations between inherited genetic variants and various human traits, ranging from height to clonal hematopoiesis. Prior to these projects, I had always thought of myself as a tool-builder. I developed statistical methods to help answer questions in genetics, but I left the application of these methods to the “real” geneticists. I was quite shocked the first time that my analyses uncovered new biological knowledge that neither I nor any of my collaborators expected. But these new findings made sense, could be validated, and were ultimately very satisfying. These experiences have shifted my path substantially, increasing my appetite for taking on projects driven by biological questions rather than only method development, and leading me to pursue several projects investigating genomic structural variation.” Loh’s current interests include studying very rare coding variants and genomic structural variants using computational methods that leverage haplotype sharing withing biobank cohorts, as well as developing methods to detect mosaic chromosomal alterations and understand how they relate to cancer and other genetic disorders. He is irrepressibly enthusiastic and curious and said, “At the moment, I am particularly intrigued by the potential to leverage population-scale whole-genome sequencing to learn more about genomic variants that have typically been difficult to ascertain – specifically, structural variants and somatic variants. However, I would not be surprised if I find myself working on entirely new research directions five years from now. My trajectory thus far has been greatly influenced by serendipitous encounters, and given the rate at which new “omic” data sets and data types become available, it seems essential to keep an eye out for important new resources and the challenges and opportunities they bring.” Loh is deeply appreciative of his mentors Berger and Price, and he recognizes their investment in him as a scientist, which included helping him identify projects that leveraged his existing skills, pushing him to expand his skills and knowledge, and helping him chart a path to independence. Soumya Raychaudhuri and Richard Maas have also been instrumental in guiding Loh through the establishment of his independent research group. His mentorship has deeply shaped how he works with graduate students and postdocs in his lab. As an early career scientist, Loh has been extremely productive, with over 70 publications, >17,000 citations and numerous awards and fellowships. Loh has consistently developed open-source software tools that are used by the computational biology community, and he has served on program committees for ISMB and RECOMB. Loh is particularly grateful for his recognition with the Overton Prize and said, “It is an incredible honor to receive this award. When I first attended the ISMB conference as a graduate student ten years ago, I never imagined I could one day be selected for the Overton Prize. I am tremendously grateful to all the mentors, collaborators, and trainees who contributed to the work recognized by this award and to my development as a scientist.”

Each year, ISCB recognizes a scientist who is within two decades of completing her or his graduate degree and has made significant contributions to field of computational biology. The 2022 ISCB Innovator Award winner is Dr. Núria López-Bigas, Group Leader and ICREA Research Professor of the Biomedical Genomics Group at the Institute for Research in Biomedicine, Barcelona, Spain. She will receive her award and give a keynote address at the 30th Conference on Intelligent Systems for Molecular Biology (ISMB) in Madison, WI being held from July 10-14, 2022. Núria López-Bigas: Taking Aim at Cancer Núria López-Bigas was born in Monistrol de Montserrat, a small town near Barcelona and had very broad interests as a young child, but her inclination toward biology emerged as a high school student, after which she pursued a B.Sc. in Biology at the University of Barcelona. López-Bigas went on to complete her Ph.D. in Biology at the Oncologic Research Institute, University of Barcelona under the mentorship of Xavier Estivill. Her dissertation research focused on the molecular causes of hereditary deafness, and she gained experience tackling questions in Mendelian genetics and validating findings in mouse models of deafness. In 2002, López-Bigas shifted her interest toward computational biology and pursued a postdoc at the European Bioinformatics Institute (EBI) in Cambridge, England under the mentorship of Christos Ouzounis. She recalled the effort that accompanied this shift and said, “It was a different time and there were very few formal training opportunities in bioinformatics, so I had to teach myself how to code.” López-Bigas’s work focused on computational comparative genomics at a time when only a handful of complete genomes existed, and she studied mutations involved in disease, much in the vein of her Ph.D. research on hereditary deafness. She also developed experience in using and analyzing microarrays. López-Bigas was supported by the Human Frontiers Science Program (HFSP) as a postdoc, which supported her research at EBI for two years, then provided her with an opportunity to pursue a project in her home country for the final year. She returned to Spain for this period and joined the laboratory of Roderic Guigó at the Centre for Genomic Regulation in Barcelona, Spain. López-Bigas began her career as an independent scientist in 2006 and was selected to be a Group Leader and Ramon y Cajal Researcher at the Universitat Pompeu Fabra in Barcelona, Spain. This position was organized as a five-year contract and included only minimal financial support to start her lab, but she also obtained a HFSP Career Development Award which provided some extra funding to get started. López-Bigas recalled, “I started slowly, and focused only on computational biology, no wet lab, and this really helped me make progress.” Her lab studied cancer genetics and they focused on copy number alterations and expression differences because of the availability of arrays and techniques that could measure these genetic features. And then the first cancer genomes were starting to be sequenced. López-Bigas recalled, “It was clear there were lots of mutations in tumors, and we thought it was important to understand how these mutations appear and which ones cause cancer across cancer types.” This research led to her interest in identifying mutations that drive tumorigenesis, and her group has published several pivotal studies detailing how different mutational processes affect specific cells and tissues, and how defects in DNA damage repair pathways alter mutation rates. López-Bigas and her team have also been at the forefront of developing software and data infrastructure for cancer research, including their IntOGen pipeline that has been used to build a compendium of mutational cancer driver genes (www.intogen.org), which provide critical insights into mechanisms that contribute to tumorigenesis. They have also developed the Cancer Genome Interpreter tool that is used to evaluate the biological and clinical impacts of mutations detected in tumor samples and guide treatment (www.cancergenomeinterpreter.org). After the 5 year contract, in 2011, López-Bigas was selected as an ICREA Research Professor, which is a permanent position paid by the Catalan government. In 2016, López-Bigas and her research group moved to the Institute for Research in Biomedicine (IRB Barcelona). She has expanded her computational biology lab and has built up a wet lab to give her group the ability to generate their own data and not be only dependent on publicly available datasets. With these expanded capabilities, López-Bigas is now using deep sequencing to compare tumor tissue and resected non-tumor tissue from the same patients to gain insight into cancer driver mutations and how small clonal cell clusters might undergo positive selection and turn into tumors. The COVID-19 pandemic temporarily shut down López-Bigas’s wet lab, but her group was able to continue their computational biology studies since each lab member had a laptop and the ability to connect to the computer cluster. In addition, López-Bigas stepped forward with her team to use their genomics knowledge to help analyze SARS-CoV-2 viral sequences in 2020. She collaborated with scientists in Austria, including Christoph Bock and Andreas Bergthaler, to carry out a genomic epidemiology study of superspreader events and understand factors contributing to mutational dynamics and viral transmission. Members of her team also helped build up the SARS-CoV-2 PCR testing infrastructure in Spain. López-Bigas and her team have now returned full focus on cancer genomics research but were gratified by the opportunities to use their scientific knowledge and skills to help during the pandemic. López-Bigas has been thankful for her mentorship as a young scientist, which provided her with both intellectual freedom and opportunities to learn new skills. As the mentor of numerous postdocs and students, she has worked hard to create a lab environment where trainees are engaged and collaborative. She said, “As a mentor, I try to get people excited about their projects, motivate them, and encourage collaboration within the lab. An important part of my job is to make the right environment so people can jump into the lab, learn from each other and do interesting science.” As a leader in the field of computational cancer biology, López-Bigas has served her peers in various capacities, including organizing several meetings related cancer genomics and sequencing for ISMB. She has served as a reviewer of grant proposals and research articles and has been a member of scientific advisory boards of large institutions such as the Finland Institute of Molecular Medicine, the Gustave Roussy Cancer Institute and Open Targets. Her work and service have been recognized by numerous awards and honors, including election as a member of European Molecular Biology Organization (EMBO) and a Fellow of ISCB. She is deeply touched by her recognition with the 2022 ISCB Innovator Award and said, “I was surprised to be selected and humbled and happy. It means the bioinformatics community appreciates and recognizes the work of my group.”

Each year, the Outstanding Contributions to ISCB Award recognizes an ISCB member for noteworthy service contributions toward the betterment of ISCB through exemplary leadership, education, and service. The 2022 Outstanding Contributions to ISCB Award recipient is Reinhard Schneider. Reinhard Schneider is Full Professor in Bioinformatics, Head of Bioinformatics Core Facility, and Head of the ELIXIR Luxembourg Node at the University of Luxembourg. His research interests include developing and improving algorithms related to structure/function predictions of proteins. Schneider has devoted more than 20 years of service to ISCB in various capacities. He became an ISCB member in 1997 but became more involved as a co-organizer of ISMB with Thomas Lengauer in 1999. Schneider joined the ISCB Board of Directors in 2005 at a time when the Society was experiencing financial turmoil. His experiences working with startups helped him work with other board members to improve the management and financial stability of the organization. Schneider worked with Bettina Roth to redesign the ISCB web portal and improved features related to membership and registration, thus making the member portal user-friendly and reliable. Schneider introduced an option for members to purchase multi-year memberships, and he helped introduce other member benefits, and together these strategies boosted both membership and revenue. Schneider served as ISCB Vice President from 2005 to 2009 and ISCB Treasurer from 2009 to 2016. His time as treasurer included developing an investment strategy for a portion of ISCB funds, which has given the Society greater financial stability. Beyond these roles, Schneider has served on various committees related to ISCB’s annual meetings, including ISMB/ECCB2007 (Vienna), ISMB2008 (Toronto), ISMB/ECCB2009 (Stockholm), ISMB2010 (Boston), ISMB/ECCB2011 (Vienna), ISMB2012 (Long Beach), ISMB/ECCB2013 (Berlin), ISMB2014 (Boston), and ISMB/ECCB2015 (Dublin). He has co-organized several international ISCB affiliated meetings in Africa, Asia, and Latin America, including ISCB Africa (2010: Bamako, Mali; 2011: Cape Town, South Africa) in cooperation with the African Society for Computational Biology and Bioinformatics (ASBCB), ISCB Latin America (2010: Montevideo, Uruguay; 2014: Belo Horizonte, Brazil), and most recently ISCB Asia (2011: Kuala Lumpur, Malaysia; 2012: Shen Zhen, China; 2013: Seoul, South Korea). His involvement with meeting organization includes helping launch and support the live coverage of ISMB via microblogging, making it one of the first life science conferences providing coverage in this manner. This initiative was started at ISMB2008 in Toronto and continues today. Schneider is deeply gratified by his work in helping establish the ISCB Student Council (ISCBSC). He said, “It was great to see the enthusiasm of younger people getting involved in ISCB and to help them establish the ISCBSC with its own activities. I have invited very good students from developing nations to my lab through the ISCBSC internship initiative and hope these types of programs can help students launch their careers.” Schneider is thankful for his diverse experiences with ISCB and encourages trainees to seek similar opportunities. He said, “It is important to learn skills that are outside of a typical graduate program, like management and organization skills, and how to work with others on different types of teams.” Schneider will be remembered as one of the ISCB’s leaders who helped financially secure the Society and broaden the ISCB membership. He will continue to support the ISCB community as a lifetime ISCB member.

The International Society for Computational Biology (ISCB) recognizes the achievements of an early to mid-career scientist each year with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, a respected computational biologist and founding ISCB Board member. The Overton Prize recognizes independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching and service. ISCB is pleased to recognize Dr. Jian Peng, Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign as the 2020 winner of the Overton Prize. Peng will be presenting a keynote presentation at the 2020 International Conference on Intelligent Systems for Molecular Biology virtual meeting being held on July 13–16, 2020. Jian Peng grew up in Yichang, Hubei Province, China to parents who were both university professors. His earliest memories include taking pleasure in his time spent reading from his parents’ home library, even when he could not fully comprehend the content of some the books. He recalled, ‘My parents were college professors, who always gave me the freedom to choose what I liked to do.’ Peng was 10 years old when his parents gave him his first personal computer. He was quickly drawn to computer programming. He spent many hours teaching himself to program and read programming books on C/C++, Windows and data structures. In high school, Peng became interested in chemistry, but he returned to his early interest in computer programming while pursuing his bachelor’s and master’s degrees in computer science at Wuhan University. As an undergraduate, Peng became deeply interested in mathematical logic and its applications to programming languages and wanted to pursue this topic in graduate school. He said, ‘I didn’t find many places to study this topic. I was fortunate to meet with Professor Jinbo Xu, who was giving a bioinformatics talk at Tsinghua University and kindly showed me several fascinating papers, including his seminal work on the protein side chain packing problem. He suggested that I spend time reading textbooks on machine learning (ML), as he believed that ML would become a very useful tool in computational biology when more data become available.’ Peng went on to complete his PhD in 2013 at the Toyota Technological Institute at Chicago under Xu, where his research focused on protein structure prediction and modeling using ML methods. These methods, which are known as RaptorX and are still widely used today, have excelled at alignments of hard targets. Peng then joined Bonnie Berger’s lab as a post-doc and expanded his research scope to include systems biology and functional genomics. He recalled, ‘We have had a great time working on a variety of problems, including structural bioinformatics, compressive genomics, systems biology and disease genomics. I also really appreciated my time in the lab of (the late) Susan Lindquist, where I learned a lot from experimental and wet lab biologists and found ways to help address important problems in neurodegenerative diseases using my computational skills.’ He is deeply appreciative of his mentorship under Xu, Berger and Lindquist not just for the areas of research he worked on with them but also for the lessons he learned in conducting experiments correctly and with rigor. In 2015, Peng was appointed as an assistant professor in the Department of Computer Science, and affiliated with the College of Medicine, at the University of Illinois at Urbana-Champaign. Peng’s perspective in identifying new research topics has evolved with his maturation as an academic. As a student, he was more drawn to problems that he thought were highly interesting, or he was swayed by the ‘coolness’ of a method. Now Peng appreciates that his research interests must also address important scientific problems, and he feels it is critical to convey this concept to his trainees as they apply their knowledge in computation and biology to solve problems that deeply interest them. Through his research experiences, Peng has learned that scientists are often surprised by unexpected findings. He said, ‘What I’ve learned in these years from successes and failures is how capable (and incapable) computational methods can be. Like many artificial intelligence/ML researchers, I was initially focused on developing powerful ML models for problems with large datasets, which hopefully can provide us new biological insights. However, in many important problems, such as those related to protein function and design, disease mutations studies and functional genomics, the effective sample sizes are much smaller than what we expect for ML.’ Peng’s research has always been driven by understanding the sequence-structure-function relationship. Currently, Peng’s research has shifted directions toward using biological insights for developing advanced ML models. Like Bayesian methods, he uses known biological insights to serve as the ‘structural’ prior to constrain ML models and generate new hypotheses in line with existing knowledge. Two recent notable projects in this line are the DeepContact algorithm for protein contact map prediction and the Mashup algorithm (with Berger and Cho) for heterogeneous biological network data integration. He is interested in understanding the functional and structural consequences of protein mutations. Peng appreciates the importance of this area in terms of designing proteins with better and more biologically relevant functions, but also improving the annotation of missense mutations in human genomes for gaining insights in molecular mechanisms of human diseases. Peng is greatly humbled and honored to receive the 2020 ICSB Overton Prize as it is a recognition from his peers within the ISCB community, and he shares his gratitude with the mentors, students and collaborators that have brought his work to fruition.

The International Society for Computational Biology (ISCB) Innovator Award recognizes a scientist who is within two decades of completing her or his graduate degree and has made significant contributions to the field of computational biology. The 2020 awardee is Dr. Xiaole Shirley Liu, Professor of Biostatistics and Computational Biology at the Harvard T.H. Chan School of Public Health and Co-Director of the Center for Functional Cancer Epigenetics at the Dana-Farber Cancer Institute. Liu will be recognized for her award and deliver a keynote presentation at the 2020 ISMB virtual meeting on July 13–16, 2020. X. Shirley Liu grew up in Tianjin, China and her elder brother sparked her interest in biology at an early age. She transferred from Peking University during her freshman year to pursue her undergraduate degree at Smith College in the USA. Liu was working toward a degree in biochemistry when she took a basic computer literacy course. From that class, Liu became drawn to computer programing and quickly immersed herself in computer science courses in her junior year. In summer 1996, she had a transformative experience, she recalled, ‘At the recommendations of my advisors Jeanne Powell and Steven Williams, I went to a University of Washington summer workshop in bioengineering and visited several universities in the West Coast. The visit to Stanford helped me realize how I could combine computer science and biology.’ Liu graduated summa com laude from Smith College in 1997 with a double major in biochemistry and computer science. She pursued a PhD in the nascent field of biomedical informatics, with a minor in computer science, at Stanford University. At the time, Pat Brown and Ron Davis’ laboratories developed DNA microarrays to study gene expression, transcription regulation and protein-DNA interactions. Under the guidance of her PhD advisors Douglas Brutlag and Jun Liu, she developed algorithms for finding protein-DNA binding motifs (BioProspector, MDscan and MotifRegressor) from co-expressed gene clusters and chromatin-immunoprecipitation microarrays. Liu accepted a faculty position right after PhD and became an assistant professor in the Department of Biostatistics and Computational Biology in the Dana-Farber Cancer Institute/Harvard School of Public Health in 2003. She recalled, ‘I was very lucky to collaborate with many wonderful colleagues at Harvard, especially with Myles Brown early in my faculty career. We share research interests in gene regulation and both believe the power of technology. Myles showed me how to use technologies cost effectively to tackle interesting biological problems, how to be open-minded when data lead us to unexpected results, and how to understand the mechanisms underlying our observations.’ They developed numerous algorithms and tools (MAT, MACS, Cistrome, LISA and MAESTRO) to model transcription factor binding and chromatin dynamics that are important to understand gene regulation in development and diseases. Liu and Brown continue to be close collaborators and have published around 70 papers together. As a member of the ENCODE consortium, Shirley Liu’s Lab continued to maintain and update these algorithms and tools, which have helped many other scientists adopt new genomics technologies and generate hypotheses. Liu became drawn to translational cancer research in 2012 after reading the Pulitzer Prize winning book, The Emperor of All Maladies, by Siddhartha Mukherjee. She had just been tenured and wanted to broaden her research areas and take more risks in her projects. Liu developed new methods (MAGeCK) to design and analyze genome-wide CRISPR/Cas9 knockout screens. Her team used computational approaches integrating large-scale compound and genetic screens, as well as functional genomics profiles from cancer cell lines and tumor cohorts, to refine our understanding of hormone receptor therapies, epigenetic inhibitors, gamma-secretase inhibitors, receptor tyrosine kinase inhibitors and immune checkpoint inhibitors in different cancers. She also developed novel algorithms TIMER and TRUST to comprehensively characterize tumor-infiltrating immune cells and immune receptor repertoires in over 10 000 tumors from The Cancer Genome Atlas. Liu continues to make significant contributions to cancer gene regulation. Liu is the principal investigator of the Cancer Immunologic Data Commons, a part of the NCI Cancer Moonshot project that aims to develop better cancer immunotherapy biomarkers and optimize treatment strategies. Liu considers her role as a mentor to be a critical part of her job. She said, ‘I want trainees to explore projects that build on their interests and previous expertise and combine that with my lab’s knowledge on gene regulation. This helps each trainee to develop a unique identity.’ She has already mentored 18 trainees who have moved on to tenure track faculty positions and continues to welcome a diverse array of trainees with computational and experimental expertise. Liu is a highly cited researcher with a prodigious publication record that includes more than 200 papers published by her group, many of them in high-profile journals and highly cited. Liu has served on the editorial boards of leading genomic and computational biology journals throughout her career. She has also served on a number of conference organizing committees and study sections. She received the Sloan Research Fellowship (2008), has been a Breast Cancer Research Foundation Investigator (2017) and became a Fellow of ISCB (2019). Liu’s open-access resources were recognized with the Benjamin Franklin Award for Open Access in the Life Sciences in 2020. Liu feels deeply honored to be recognized with the ISCB Innovator Award, especially as it comes from her peers in computational biology. She is inspired to continue pursuing projects that advance our understanding of basic biology and can be translated into clinical benefits to cancer patients.

The Outstanding Contributions to IISCB honors a leader in the fields of computational biology and bioinformatics each year with the Accomplishments by a Senior Scientist Award. This award is the highest honor conferred by ISCB to a scientist who is recognized for significant research, education, and service contributions. Steven L. Salzberg, Bloomberg Distinguished Professor of Biomedical Engineering, Computer Science and Biostatistics at Johns Hopkins University and Director of the Center for Computational Biology, is being honored as the 2020 winner of the ISCB Accomplishments by a Senior Scientist Award. He will be recognized and give a keynote address at ISMB 2020 virtual conference being held on July 13–16, 2020. Steven Salzberg grew up in Columbia, SC. Throughout his childhood and young adulthood, he was always interested in science and deeply enjoyed reading science fiction. Salzberg was also fascinated by astronomy and considered studying physics. As an undergraduate at Yale University in the 1970’s, he explored several majors and thought he had settled on English Literature but added Computer Science as a second major upon taking an introductory computer programming class. He recalled, ‘This is the kind of math I thought I would really like to study’, and he was soon captivated by artificial intelligence (AI) and natural language processing. At the advice of his undergraduate advisor, Salzberg spent a year after graduation gaining more programming experience by working at a local power company in South Carolina, where he worked on an IBM mainframe and used self-training courses to learn COBOL and IBM assembler. Salzberg said, ‘It was a very boring sort of application, but I was still interested in programming. I liked the idea I could work on something technical and within a short period of time, I would have results that would do what I intended’. Salzberg returned to Yale and completed his M.S. in computer science. He then joined a startup in Boston during the first blush of AI, although this and many other AI startups failed in the late 1980’s due to lack of computing power and other technical limitations. One of Salzberg’s advisors at the startup was AI pioneer Bill Woods, who held an adjunct appointment at Harvard University and later became Salzberg’s graduate advisor in the Department of Computer Science. Salzberg had managed to avoid taking any biology classes as an undergraduate, but he heard about the Human Genome Project (HGP) while he was in graduate school in the late 1980’s. He said, ‘The Human Genome Project sounded like the most exciting thing in all of science at the time, and I wanted to be a part of that’. While completing his PhD project in machine learning, he started sitting in on biology classes, including a course by the late Stephen Jay Gould and reading on his own to learn about genomics and genetics. He was determined to figure out a way to using his computing knowledge to get involved in the HGP. Salzburg continued doing research in machine learning as he started in his first academic position at Johns Hopkins University. He was still curious about genomics and recalled going to a talk in the early 1990’s by Temple Smith about sequence differences between exons and introns. It dawned on Salzberg that he could use machine learning to distinguish exons from introns, which could be used as a strategy for gene finding. This became Salzberg’s entrance into genomics. During this time, Salzberg was also introduced to Nobel Laureate Hamilton Smith, a notable microbiologist who discovered type II restriction enzymes. Salzberg recalled, ‘[Smith] had a secret passion for computer programming. He wanted to talk to computer scientists who were interested in genomics—that was me. And I was interested in learning more about genomics’. Salzberg and Smith began working together to understand how computer programs could be made for tasks like gene finding. Smith had also started collaborating with J. Craig Venter, and in 1997, both Smith and Salzberg began working at Venter’s non-profit research institute, The Institute for Genomic Research (TIGR). Salzberg became the Director of Bioinformatics at TIGR and developed with his colleague Art Delcher the GLIMMER gene finder, a software system still used today to identify coding regions in bacteria, archea and viruses. In the early 2000’s, the first Mycobacterium tuberculosis genomes were being sequenced by both TIGR and The Sanger Center. This led Salzberg and his colleagues to develop MUMmer, a system that could be used to compare large genomes. He also got involved in the HGP through the development of a gene finder that could analyze the human genome and, with his colleague Mihaela Pertea, also built other eukaryotic gene finders for plant, fungus and parasite genomes. Salzberg and his colleagues were called upon by the FBI after the 2001 anthrax attacks to analyze the genome of the anthrax bacteria, and that work identified genetic mutations that eventually pinpointed the source of the bacteria to a biodefense lab in Fort Detrick, Maryland. In 2003, Salzberg co-founded the Influenza Genome Sequencing project with David Lipman, which involved the sequencing and analysis of thousands of influenza isolates. Salzberg then moved to the University of Maryland, College Park in 2005, where he was the Horvitz Professor of Computer Science. He returned to JHU in 2011, where he is currently the Bloomberg Distinguished Professor of Biomedical Engineering, Computer Science and Biostatistics and the Director of the Center for Computational Biology in the Whiting School of Engineering. As next-generation sequencing technology developed, Salzberg’s research interests shifted toward developing algorithms for large-scale genome assembly and sequence alignment, including the development of the open-source Tuxedo suite of programs (Bowtie, Tophat and Cufflinks). Salzberg’s current interests include the development of an improved human gene catalog and assembly and annotation of an Ashkenazi human reference genome. Recent technical advances have made this undertaking feasible, and the research community has desperately needed other reference genomes beyond the only publicly available genome, GRCh38. Salzberg is also working with colleagues on developing methods for using shotgun sequencing as a diagnostic tool for infectious diseases. They have tested their techniques on biopsy materials from patients with difficult-to-diagnose brain infections and on samples collected from eye infections, and the technology has the potential to work on a much broad range of infections. Salzberg has trained numerous students and post-doctoral fellows throughout his time in academia and at TIGR, and he has focused on matching highly motivated individuals with projects that get them excited. Like many computational biologists, Salzberg is continually in search of interesting data associated with problems that matter, whether they involve the nature of the human genome, human health and disease, or any of a much broader range of microbial, plant and animal genomes. Salzberg’s body of work includes more than 300 publications, including many highly cited manuscripts. His contributions have been recognized through his election as a member of the American Academy of Arts and Sciences, a Fellow of the American Association for the Advancement of Science, a Fellow of the International Society for Computational Biology (ISCB) and a member of the Board of Scientific Counselors of the National Library of Medicine at NIH. All of Salzberg’s bioinformatics systems have been released as free, open-source software and he won the 2013 Benjamin Franklin Award for Open Science for his advocacy of open-source software and of open sharing of genome sequence data. Salzberg is also a contributor to Forbes magazine and writes a widely read column that debunks pseudoscience and explains scientific and medical findings with honesty and clarity. Salzberg is greatly honored to be the 2020 recipient of ISCB’s Accomplishments by a Senior Scientist award. He has always felt at home at ISMB meetings since their inception and is touched by this award since it is bestowed upon him by his computational biology colleagues.

The Outstanding Contributions to the International Society of Computational Biology (ISCB) Award recognizes outstanding service contributions to the Society by any member through exemplary leadership, education, service, or a combination of these three elements. Judith Blake, Professor at the Jackson Laboratory in Bar Harbor, ME, USA is the 2020 winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2020 ISMB virtual meeting being held on July 13–16, 2020. Judith Blake has spent most of her career at the Jackson Laboratory in Bar Harbor, ME, USA developing bioinformatics systems for integrating genetic, genomic and phenotypic information and working to make data from different genomes more accessible for genomics and genetics research. Early in Blake’s career at the Jackson Laboratory, she became a principal investigator with the Mouse Genome Informatics (MGI) project, a widely used international open access database resource for the laboratory mouse, providing integrated genetic, genomic and biological data to facilitate the study of human health and disease. Blake’s work on the MGI led to her interest in bio-ontologies. During the 1998 ISMB meeting, she and other colleagues working on genome projects in different model organisms recognized a need for open access bio-ontologies, which are controlled structured vocabularies for molecular biology that support the comparison of data across different genomes. She is one of the founding principal investigators and one of current leaders of the Gene Ontology (GO) Consortium group. Together with her research team, she has spent many years contributing to development of bio-ontology systems and to supporting integration of functional genomics data for mouse, in particular, within MGI and the GO project. Beyond Blake’s contributions to the bioinformatics and data curation communities, she has served ISCB in many ways. She recalls attending the first ISMB meeting at the National Library of Medicine in Bethesda, MD, USA in 1993, which led to the eventual formation of ISCB. Blake said, ‘Here, I found a community of investigators actively engaged in creating new tools and approaches to computational scientific investigations. My colleagues in ISCB shared my excitement as new innovations were developed to understand molecular systems and data’. She has come to appreciate how ISCB brings together scientists from academia, industry and technology in an open and supportive environment that fosters the building of new tools to advance the understanding of biological systems. Blake has served on the ISCB Board of Directors and chaired the ISCB Public Affairs and Policy committee, as well as working on other program and review committees. She has also represented ISCB on the Federation of American Societies for Experimental Biology Board of Directors. Blake sees many benefits in pursuing scientific service opportunities and said, ‘I encourage young scientists and trainees to engage in those ISCB activities that match their passions. The opportunity to support their colleagues and to engage in a scientific network will both enhance the interactions of a global network of scientists but will also bring new insights to their own scientific investigations’.

Annually, the International Society for Computational Biology (ISCB) recognizes three outstanding researchers for significant scientific contributions to the field of bioinformatics and computational biology, as well as one individual for exemplary service to the field. ISCB is honored to announce the 2021 Accomplishments by a Senior Scientist Awardee, Overton Prize recipient, Innovator Awardee and Outstanding Contributions to ISCB Awardee. Peer Bork, EMBL Heidelberg, is the winner of the Accomplishments by a Senior Scientist Award. Barbara Engelhardt, Princeton University, is the Overton Prize winner. Ben Raphael, Princeton University, is the winner of the ISCB Innovator Award. Teresa Attwood, Manchester University, has been selected as the winner of the Outstanding Contributions to ISCB Award. Martin Vingron, Chair, ISCB Awards Committee noted, 'As chair of the Awards Committee it gives me great pleasure to convey my heart-felt congratulations to this year's awardees. Our community, as represented by the committee, admires these individuals' outstanding achievements in research, training, and outreach.'

ISCB honors a leader in the fields of computational biology and bioinformatics each year with the Accomplishments by a Senior Scientist Award. This award is the highest honor conferred by ISCB to a scientist who is recognized for significant research, education and service contributions. Bonnie Berger, Simons Professor of Mathematics and Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), is the 2019 recipient of the Accomplishments by a Senior Scientist Award. She is receiving her award and presenting a keynote address at the 2019 Joint International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology in Basel, Switzerland on July 21–25, 2019. Bonnie Berger grew up in Miami, Florida with her parents and older brother and has early memories of being curious about mathematics. She recalled, ‘As a young child, I responded, ‘I want one too, please’, when my father slipped math problems under my brother’s door. My father would continue to challenge me with math riddles and chess puzzles. He would also engage me in science projects. Our relationship laid the foundation for my comfort with, and interest in, math and science, even though it was not so common for girls at the time’. Berger’s early interest in math and science led her to complete her AB in computer science at Brandeis University. In 1990, she completed her PhD in computer science at MIT under the mentorship of Silvio Micali. Berger’s dissertation research on randomized and parallel algorithms was recognized by the Machtey Award for a manuscript that she co-published with fellow graduate student John Rompel, as well as the George M. Sprowles Award. After graduate school, Berger remained at MIT and stumbled upon computational biology quite unexpectedly. She recounted, ‘My postdoc supervisor Daniel J. Kleitman, who has Erdos #1 and solved dynamic programming for RNA base-pairings with Ruth Nussinov, had just come back from an NSF workshop whose goal was to get mathematicians and biologists together to solve challenges at the interface between the two fields. He was so taken with Michael Levitt’s talk that he said, ‘Proteins, that’s what you should do’. Well, fortunately, he didn’t say, ‘Plastics’, as in ‘The Graduate’, or I might have ended up a material scientist’. She appreciates the freedom she had as a postdoc and took to heart the advice Kleitman gave her when he told her, ‘We are applied mathematicians looking for interesting problems to investigate’. Following her postdoc, Berger became an Assistant Professor of Mathematics at MIT, and as a PI, she has pioneered the use of computer algorithms for analyzing, interpreting and sharing diverse types of biological data. Among Berger’s scientific contributions, she developed the use of pairwise residue correlations to predict protein structure from sequence through her highly cited Paircoil/Multicoil programs. Her seminal work on the hardness of protein folding was recognized with the 2010 RECOMB Test of Time Award. Berger’s interest in genomics included development of the ARACHNE genome assembly tool, which was used by the Human Genome Consortium for whole genome assembly. She also initiated the area of comparative genomics with her cutting-edge work comparing human and mouse genomes. Berger launched the subfield of global network alignment with her Isorank/IsorankN programs and advanced protein structure alignment with her MATT program. More recently, Berger has founded the field of compressive genomics by designing algorithms that can be used for genomic analysis on compressed data in order to keep pace with data generation. She has also spearheaded efforts to improve biomedical data privacy, including the development of tools to securely crowdsource genomic and pharmacological data at scale. Berger considers her theoretical computer science background to be critical to her success in identifying and studying computational biology problems. She said, ‘I have realized that with my algorithms background and flexibility, I can easily shift between areas as the research landscape changes. As I gain knowledge across diverse research areas, I can see connections between them and techniques that can be used to address them’. Berger has also come to appreciate the many mentors that helped her bridge the gap between computer science and biology, including Peter Shor, Peter S. Kim and Jonathan King. She recalled, ‘[They] taught me biology on a need-to-know basis. It took many rounds of back-and-forth by, would you believe, fax machine with Peter Kim for me to turn my early Paircoil writeup from definitions and theorems to one accessible to a biology audience’. Berger has trained numerous graduate students and postdocs, using an approach she learned from her NSF Postdoc supervisor. She said, ‘[Kleitman] gave me a lot of freedom to pursue whatever interested me, and that’s how I mentor my students. I ask them what interests them and suggest several research problems, or I encourage them to bring entirely new research areas to us’. Many of her trainees have become leaders in the field of computational biology. Berger is also fascinated by developing methods to improve data sharing and said, ‘I am interested in individuals, labs and companies owning rights to their own data but providing provably secure algorithms so that they can for the first time share their data at scaleto enable biomedical insights across different nations and diverse data. Recently, I am interested in developing sketching algorithms that take advantage of the geometry of single-cell RNA-seq data to better share, analyze and draw insights from the data’. Berger has served the computational biology community in many capacities, including her roles as Vice President of ISCB and Head of the RECOMB Steering Committee; as well as her service on multiple editorial boards, and program and conference committees. Her scientific contributions have been recognized by numerous awards, including the NSF Career Award, Biophysical Society Dayhoff Award for Research, inaugural Technology Review Top 100 Innovators, ACM Fellow, ISCB Fellow, AMS Fellow, AIMBE Fellow, NIH Margaret Pittman Award for Outstanding Scientific Achievement & Lectureship, election to the American Academy of Arts & Sciences and an Honorary Doctorate from EPFL. Berger is extremely grateful for this recognition by ISCB, especially considering her longtime involvement with the Society. She said, ‘It’s a tremendous honor to join such a distinguished and accomplished group of scientists’.

Abstract

The Outstanding Contributions to the International Society of Computational Biology (ISCB) Award recognizes outstanding service contributions to the Society by any member through exemplary leadership, education, service or a combination of these three elements. Barbara (Barb) Bryant, Senior Director at Constellation Pharmaceuticals, is the 2019 ISCB winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2019 Joint Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Basel, Switzerland on July 21–25, 2019. Barb Bryant has spent much of her career as a computational biologist working in the pharmaceutical industry, where she has managed and directed a wide array of bioinformatics projects related to cancer diagnostics, clinical biomarker identification and mechanism of action of small molecule inhibitors. Bryant first became involved with ISCB by attending conferences like ISMB and engaging in leadership opportunities through ISCB. She has continued to be involved with ISCB because she has benefited and genuinely treasured being a part of this unique community. She said, ‘I have enjoyed working with colleagues to find ways to support other computational biologists, particularly students and postdocs. It was great to have a shared purpose, in contrast to the somewhat competitive nature you can sometimes find in scientific research. It is gratifying to be able to see progress on community projects such as nurturing the Student Council, encouraging open sharing of data and software, putting on conferences or developing publishing venues. Above all, I value the friendships that I have developed with others on the Board and Committees’. Bryant has served on the ISCB Board of Directors in several capacities, including ISCB Secretary (2002–2005) and Vice President (2005–2007). She also chaired the Public Affairs Committee during this time and was instrumental in maintaining ISCB’s affiliation with FASEB. Bryant worked on the Editorial Board of PLoS Computational Biology and has been thankful for these diverse service opportunities. She said, ‘I loved collaborating with Phil Bourne on the Editorial Board of PLoS Computational Biology. It is great to work with colleagues who have a ton of great ideas and an inclusive, forward-looking attitude. Thinking about how to bring positive change on the Board and within the Society has also been a good challenge. I appreciated serving as the representative of ISCB to FASEB in order to have a voice in Washington at a critical time, post-9/11, when it was becoming harder to travel to the USA for scientific conferences and collaboration’. Bryant sees ISCB playing a critical future role in advancing important initiatives related to computational biology, including advocating for improved research funding and open access to findings from government funded research. She considers one of ISCB’s strengths to be in the exchange of scientific information through conferences and publications, and she hopes the Society can continue to innovate novel approaches to enhance the communication and dissemination of computational biology research. Bryant hopes trainees and junior faculty members seek out constructive service opportunities with ISCB and other similar organizations. She said, ‘There are two key aspects of serving that I think matter even more than the particular area of service. The first is to find a way to make a positive difference—to change how the world operates. The second is to do it with other people who are positive and effective and fun to be with. If it is a toxic environment, leave. If the people are awesome, stick with it and find a way to contribute, no matter how hard the problem!’ Bryant will be recognized for her distinguished service to ISCB at the 2019 Joint ISMB/ECCB conference in Basel, Switzerland alongside this year’s other ISCB award recipients.

The ISCB Innovator Award honors an ISCB scientist who is within two decades of having completed his or her graduate degree and has made outstanding contributions to the field of computational biology. The 2019 winner is Dr. William Stafford Noble, Professor in the Department of Genome Science, University of Washington. Noble will receive his award and deliver a keynote presentation at the 2019 Joint International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology in Basel, Switzerland being held on July 21–25, 2019. William Stafford Noble was raised in Naperville, IL, with his brothers and his parents who were both college professors. As a child, he didn’t have a specific interest in science, but he remembered, ‘I was just interested in learning stuff’. A simple test gave Noble a peek into his future career path. Noble recalled, ‘I took a career aptitude test in high school, and the results said I should be a college professor or computer scientist, but at that point I had never touched a computer’. Noble went to Stanford University to complete a bachelor’s degree in Symbolic Systems, with a concentration in Philosophy. He has come to appreciate the multidisciplinary nature of his undergraduate degree, which included a broad range of coursework in computer science, cognitive science, linguistics, philosophy and mathematics. After graduating in 1991, Noble gained work experience in the field of speech recognition, and he also spent two years in the US Peace Corps in Lesotho, Africa. Noble said, ‘Both of my brothers went overseas after college, so I picked the Peace Corps. It seemed to be a little better organized than some other options’. Noble spent two years teaching math, physics and English literature to secondary students and had to develop teaching skills to explain complex material in a clear and straightforward way, training that has served him well throughout his career. All the while, he kept thinking about computer programming, and he would write down programs on paper in his free time. At the end of his first year in Lesotho, his parents visited him and brought him a laptop, so he could use the brief hours of evening electricity to transfer his programs from paper to a computer. Noble also developed an interest at this time in artificial life, which was a relatively new field. He got his hands on several artificial life conference proceedings and set off to study this area as a newly minted graduated student at the University of California, San Diego in 1994. Relatively quickly, he came to feel that this field was too descriptive, so he began to search for a different dissertation subject. His future Ph.D. mentor, Charles Elkan, emailed him about a funding opportunity that would allow him to study hidden Markov models (HMMs) in protein and DNA sequences. Noble was open to this topic because he was already familiar with HMMs from his work in speech recognition, and he went on to complete his Ph.D. in computer science and cognitive science in 1998. Noble’s first bioinformatics publication, which was based on his Ph.D. research, described a web server for motif-based sequence analysis (the MEME Suite) that is still in use today. Noble went on to David Haussler’s lab at the University of California, Santa Cruz as a Sloan/DOE postdoctoral fellow and co-authored the first paper that applied support vector machines to microarray gene expression data. He also developed kernel functions that could be used to represent a variety of data types, and he showed how kernels could be used to perform inference jointly from these heterogenous types of data. This work was ultimately developed into applications in inference of protein-protein interactions and gene function that are used by many researchers. In 1999, Noble became an Assistant Professor in the Department of Computer Science at Columbia University, with a joint appointment at the Columbia Genome Center. He moved to his current appointment at the University of Washington in 2002 in the newly formed Department of Genome Sciences with adjunct appointments in the Department of Computer Science and Engineering, the Department of Medicine and the Department of Biomedical Informatics and Medical Education. As an independent investigator, Noble has expanded his research interests including the development of unsupervised machine learning methods for semi-automated genome annotation, and the application of machine learning and statistical methods to analyze proteomic data. He has also worked with collaborators to develop high-throughput assays to characterize the 3D structure of DNA in the nucleus. Throughout his career, Noble has grown as a scientist and mentor by learning from those who have mentored him, as well as observing how his collaborators mentor students and run their labs. Noble also credits his wife, Nancy Stafford Noble, for being a valuable sounding board and providing her expertise as an executive coach as he has navigated the many challenges of being a PI. Noble’s prodigious body of work includes authorship of over 230 peer-reviewed articles. He has trained and advised 15 graduate students and 21 postdoctoral fellows, many of whom now hold faculty appointments, and he was honored with the Postdoc Mentor of the Year Award by the University of Washington Postdoctoral Association. Outside of the lab, Noble is an active member of the global computational biology community through his service on multiple editorial boards, conference committees, study sections and roles on the ISCB Board and various committees. Noble has been a part of ISCB since its early years and has always felt at home at ISMB meetings, which he considers one of the few gatherings that brings together computational biologists who bridge the gap between basic computer science and applications in biology. Noble feels deeply honored by his recognition with the 2019 ISCB Innovator Award, particularly as this award is bestowed upon him by colleagues for whom he holds great respect and admiration.

Each year the International Society for Computational Biology (ISCB) recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, a respected computational biologist and founding ISCB Board member. The Overton Prize recognizes independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching, and service. ISCB is pleased to recognize Dr. Cole Trapnell, Assistant Professor of Genome Sciences at the University of Washington as the 2018 winner of the Overton Prize. Trapnell will be presenting a keynote presentation at the 2018 International Conference on Intelligent Systems for Molecular Biology in Chicago, Illinois being held from July 6 to 10, 2018. Cole Trapnell’s earliest interest in science began at home. He was born in Cheverly, MD and spent his childhood living in College Park, right near the University of Maryland. His father, Bruce Trapnell, is a physician scientist, and Cole has fond memories of accompanying his father to the lab. Beyond the hands-on experiences of doing restriction digests with his dad as young child, Trapnell most appreciates how his father encouraged him to think scientifically. He recalled, ‘One time we were playing a board game, and I remarked that because the last dice roll was a six, the next one wouldn’t be. My dad decided to correct my thinking, so the next thing I knew, we were flipping a penny 1000 times to estimate the probability distribution of getting heads versus tails. I still have the plot that we drew by hand on 1 mm graph paper.’ Trapnell was first interested in physics and abstract mathematics and was drawn to how these fields tackled complex ideas in terms of ‘first principles.’ He began learning programming as a high school student and worked as a student engineer on a robotics project for the US Army. Trapnell honed his coding skills as an undergraduate by working for a startup that developed software for the areas of retail stock, futures and foreign currency trading, and he learned how to develop tools that can do complex calculations with large amounts of data in real time. He completed a dual BS degree in computer science and mathematics at the University of Maryland, College Park in 2005 and then began his PhD in computer science there as well. Trapnell thought he would work on problems in supercomputing, but then he took Steven Salzberg’s class on bioinformatics. This brought his attention to the emergence of ‘next-generation’ sequencing technology, and he realized the potential for high throughput computing to handle this sequence data. Trapnell’s PhD research focused on sequence alignment, and he adapted the Bowtie algorithm developed by Ben Langmead into a program called TopHat that could handle transcriptomic data. During this time, Trapnell moved to the University of California, Berkeley, where his wife was pursuing her PhD in mathematics, and he started working with Lior Pachter, who became his co-advisor with Salzberg at UMD. As Trapnell developed TopHat and the companion tool, Cufflinks, he tested them with datasets from Barbara Wold’s lab, and he began to develop an appreciation for biological questions, especially in gene regulation. Trapnell was drawn to doing bench research, and his labmate Rob Bradley encouraged him to take that leap. He recalled, ‘Rob Bradley convinced me that to become a really good biologist, I should learn to do experiments. Rob, who trained as a biophysicist, had gone off to do a postdoc at the bench. I followed suit and joined John Rinn’s lab (at Harvard University), where I worked to both do experiments and analyze them myself.’ Trapnell’s time in Rinn’s lab not only helped him get his hands dirty doing bench research, but gave him the unique perspective of working under a scientist who pioneered the field of long noncoding RNAs. Trapnell’s postdoctoral training opened his eyes to the realities of experimental biology and he acknowledges that these experiences have made him a better computational biologist. While Cufflinks could help him predict which individual splice isoforms may be elevated under certain disease conditions, he came to realize how hard it can be to validate these observations at the lab bench: a specific antibody may not exist for a western blot or technical difficulties may make it difficult to knock down a gene isoform in a particular model system. Trapnell had to adjust to the different culture associated with working in a wet lab. He recounted, ‘Computational people are often mystified and frustrated by how often their experiments fail. I like to tell them a story of my own frustration: A little while after starting my wet lab postdoc training, I was complaining to my labmate, Dave Hendrickson, that my experiments were constantly failing. He asked me how long I’d been at it, and I told him about six months. He said, ‘Well, give it another six months.’ I thought he meant I would get better at doing experiments but what he actually said next was, ‘It’ll hurt less when they don’t work.’ This was a tremendously eye opening thing for me, because he was trying to tell me that being an effective experimentalist means anticipating failure, planning for it, designing controls that can detect it, and parallelizing work within projects so that you can make progress in one direction even when you’re stuck in another. There are similar cultural differences that experimentalists encounter when learning to program.’ As a PI, Trapnell is supportive of students and trainees that want to gain both experimental and computational experience, but he wants to them to learn to understand the culture of these two realms and not just acquire the necessary skills to do experiments or develop algorithms. Throughout his training, Trapnell has valued the guidance of his mentors. His current lab is positioned between the labs of Stan Fields and Bob Waterson, both leaders in the field of genomics, and they been invaluable advisors to Trapnell. He said, ‘Despite their fame and their busy lives, both go way out of their way to advise me on how to bring my research and lab to its potential.’ All of his mentors have inspired Trapnell to build a lab culture that encourages open, inspiring and rigorous science. As he established his own lab at the University of Washington, he has started to think differently as a PI and said, ‘I am continually faced with the question: What do I think is the most important scientific contribution I can make?’ Shifting his mindset has been a challenge, but he is still broadly interested in gene regulation, especially gaining a more quantitative understanding of the epigenome. Trapnell considers the advances in single-cell measurements as critical to quantifying aspects of gene regulation, and his team is developing tools for single-cell measurements of gene expression, chromatin accessibility, and other features of the molecular state of the genome. Much of this work is in collaboration with Jay Shendure, whose lab specializes in molecular biotechnology development. Trapnell is keen on this collaboration: ‘Jay and I have very different approaches but share a common goal to transform our understanding of development and disease using single-cell technologies. Our collaboration has been fantastically productive and fun so far, and there’s a lot more to come.’ Trapnell is deeply honored to selected for the Overton Prize, and said, ‘I feel strongly that my success is at least as much a product of my being in the right place at the right time with the right collaborators as from any choices I made. I have been repeatedly given great opportunities and I’ve tried to make the best use of them, but I would have gotten nowhere if not for the generous help and creativity of a long list of mentors, collaborators and colleagues.’

Every year ISCB recognizes a leader in the computational biology and bioinformatics fields with the Accomplishments by a Senior Scientist Award. This is the highest award bestowed by ISCB in recognition of a scientist’s significant research, education and service contributions. Ruth Nussinov, Senior Principal Scientist and Principal Investigator at the National Cancer Institute, National Institutes of Health and Professor Emeritus in the Department of Human Molecular Genetics & Biochemistry, School of Medicine at Tel Aviv University, Israel is being honored as the 2018 winner of the Accomplishment by a Senior Scientist Award. She will receive her award and present a keynote address at ISCB’s premiere annual meeting, the 2018 Intelligent Systems for Molecular Biology (ISMB) conference in Chicago, IL being held on July 6–10, 2018. Ruth Nussinov is a computational biologist with research interests that have touched every aspect of the field, from her PhD research on RNA secondary structure prediction to her visionary work on DNA sequence analysis, to proposing that all protein (and other biomacromolecules) conformations pre-exist and that all dynamic proteins are allosteric, to her current studies focused on Ras signaling in cancer. Nussinov’s deep intellectual curiosity has guided her research interests throughout her career. Nussinov was raised in Rehovot, Israel, and attributes her early interest in science to watching her father conduct pioneering agricultural research that focused on adapting crops to the Israeli climate (http://en.hafakulta.agri.huji.ac.il/people/shmuel-hurwitz; Nussinov, 2017). Nussinov’s father, Shmuel Hurwitz was born in Minsk, Russia and studied chemistry at Moscow University but later immigrated to Palestine (present-day Israel) after his arrest for Zionist activities. It was here he discovered the great need for agricultural research. He pursued these studies at Berlin University but left Nazi Germany after his graduation in 1933 to found the Agricultural Research Station in Rehovot. Hurwitz was a founding member of the Faculty of Agriculture at the Hebrew University and was recognized for his significant contributions to advancing Israel agriculture with the 1957 Israeli Prize. As a child, Nussinov often joined her father on trips to his field sites, and his devotion to research and intense work ethic influenced her deeply and shaped how she approaches her work. Nussinov also attributes her success as a scientist to the unwavering support from her husband, Shmuel Nussinov. They married just after she completed her service in the Israeli Army, during which time he was pursuing his graduate studies in particle physics at the Weizmann Institute. Her husband’s research advisor moved to the University of Washington, so Nussinov continued her undergraduate studies there (in microbiology) and went on to pursue her Master’s degree in biochemistry at Rutgers University while her husband pursued postdoctoral research at Princeton University. They returned to Israel when Shmuel Nussinov joined the faculty at Tel Aviv University. When they came back to the USA several years later for his sabbatical, Ruth Nussinov enrolled in a PhD program in biochemistry at Rutgers and was mentored by a newly arrived assistant professor named George Pieczenik who had just come from Cambridge (UK). Nussinov recalled, ‘He said, “You know Ruth, Fred Sanger has just developed a DNA sequencing method and consequently there will be RNA sequences, and we will need an algorithm for the prediction of the secondary structure of RNA.”’ She ran with this idea and worked tirelessly to develop the foundational Nussinov dynamic programming algorithm that is still in use today (Nussinov, 1978). Nussinov’s PhD research has driven her career-long search for questions that tackle issues of biological significance. She worked relatively independently on her project and was able to graduate in two years, and this early autonomy was critical to shaping her career path as an independent researcher. Nussinov and her family returned to Israel and she pursued postdoctoral studies in the Structural Chemistry Department of the Weizmann Institute and made several seminal contributions to DNA sequence analysis. She also worked as a Visiting Scientist in the Chemistry Department at the University of California, Berkeley and in the Biochemistry Department at Harvard University. In spite of her impressive body of work and concept-driven approach to scientific inquiry, Nussinov faced difficulties in securing a position at Tel Aviv University in the mid-1980s given her husband’s existing position at the university and her unconventional, independent career path (Shehu, 2013). In 1985, Nussinov was finally appointed as an Associate Professor at Tel Aviv University and also became affiliated with NCI/NIH. During these early years, she credits her husband for giving her valuable advice about handling criticism from manuscript reviewers. He urged her to trust in her work and to reflect on and revise her manuscripts and resubmit them, as publications matter to the progress of a junior and unknown scientist (Nussinov, 2017). One of Nussinov’s most profound contributions to the field is the ‘conformational selection and population shift’ model of molecular recognition (Boehr et al., 2009; Ma et al., 1999, 2002; Tsai et al., 1999a, b). She and her colleagues first proposed this model in 1999 as an alternative paradigm to the ‘induced-fit’ model of protein–protein interactions. The induced-fit model hypothesizes that conformational changes to a protein occur in a stepwise fashion upon binding to a ligand. In contrast, the conformational selection model portends that unbound molecules exist in all possible structural conformations, but some unbound higher-energy conformations preferentially associate with a binding partner and cause a shift in equilibrium that favors this conformation. This model can explain numerous interactions observed for protein–ligand, RNA–ligand, protein–protein, protein–DNA and protein–RNA interactions, and can explain mechanisms of biological regulation, including oncogenic signaling. Nussinov is currently focused on the Ras protein and its interactions with effectors, with a particular interest in KRAS-driven adenocarcinomas. She observed that self-association of GTP-dependent K-Ras dimers at different interfaces regulates which effectors bind to the dimers, which can alter downstream activity (Nussinov et al., 2018). Nussinov and her team have also described the critical role of calmodulin selectively binding to the GTP-bound K-Ras4B oncogenic isoform, which promotes the initiation and progression of adenocarcinomas due to full activation of PI3Kα/Akt signaling in addition to the MAPK pathway. These mechanistic insights are critical to developing better cancer drugs, and this work was recognized in the ‘Best of the AACR Journals Collection 2015’. Nussinov is also starting to explore interactions between the human proteome and pathogens, given the growing appreciation of the microbiome on human health. Nussinov’s impact to the fields of computational biology and bioinformatics is notable. She has published more than 500 articles and has been ranked as a Highly Cited Researcher (ranking among the top 3000 researchers or 1% across all fields according to Thomson Reuters Essential Science Indicators, http://highlycited.com/December 2015) with more than 43 000 citations to date. Nussinov has also given over 300 invited talks and continues to maintain an active speaker schedule. Nussinov serves as the Editor-in-Chief of PLOS Computational Biology, and she has also served as an editor and reviewer for numerous leading journals. Her scientific contributions have been recognized through her election as a Fellow of the Biophysical Society (2011) and an ISCB Fellow (2013). Nussinov has been a devoted mentor and advisor to graduate students and trainees throughout her career, and she has mentored dozens of PhD students, including numerous women. She has tried to model her mentorship to how she was trained, and she said, ‘I very much encourage independence and like for students to suggest a problem to study’. Nussinov has always felt close connection with ISCB and her recognition with the 2018 ISCB Accomplishments by a Senior Scientist Award is a fitting tribute to her contributions to ISCB and to computational biology in general. She said, ‘I feel that’s where I belong and that’s where I want to be. I care very much about the development and sustainability and contribution of computational biology to all biological, chemical and physical sciences’. Conflict of Interest: none declared.

The Outstanding Contributions to International Society for Computational Biology (ISCB) Award was introduced in 2015 to recognize Society members who have made lasting and beneficial contributions through their leadership, service and educational work or a combination of these areas. Russ Altman, Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medicine Discipline), of Biomedical Data Science and, by courtesy, of Computer Science, is the 2018 winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2018 Intelligent Systems for Molecular Biology (ISMB) meeting in Chicago, IL being held on July 6–10, 2018. Altman’s years of dedicated service to ISCB began when he attended the very first ISMB meeting in 1993. As a brand new faculty member, he remembered how he felt at home at ISMB, surrounded by a community of scientists also interested in computational biology and bioinformatics. Altman’s enthusiasm at this first ISMB meeting led him to help organize the next ISMB meeting. He recalled, “It became clear that there was no obvious ‘host’ for ISMB 1994, so I volunteered to host it at Stanford, where we had a lovely meeting with a couple of hundred people. We had some extra money after paying our bills, so we wanted to send the money to wherever ISMB 1995 was going to be (UK). For the first few years, this is how ISMB worked—the organizers from 1 year would send the leftover funds as a seed for the next ISMB. There was no organization, and as the size of the leftover check increased, we started getting nervous and realized we needed to create a legal entity.” ISCB was born at ISMB 1997 in Halkidiki, Greece, where organizers of former ISMB meetings and others sat at dinner on the beach and planned the society and figured out how to incorporate it. Altman has warm recollections of that historic gathering and said, ‘There are pictures of that great dinner and group, and I treasure the memory of that meeting’. Altman has enjoyed serving ISCB at all levels since its inception, from work on the Publications Committee and as a conference organizer, to his tenure on the ISCB Board of Directors (1997–2005) and as ISCB President (2002–2005). Altman’s early work on the Publications Committee included applying for PubMED to index the ISMB proceedings, which was a critical step in helping ISCB members receive academic credit for their conference papers. Altman also helped negotiate the agreement to have Bioinformatics named as an official ISCB journal. Beyond ISMB, Altman has been an organizer of the Pacific Symposium on Biocomputing, and has facilitated the relationship between this conference and ISCB. As computational biology and bioinformatics have grown into stand-alone fields, Altman has made many critical scientific contributions through his research. Altman and his research group have developed numerous computational tools that address problems in basic biology and medicine, with a particular interest in understanding drug responses. His work has included studies of structure-function relationships in macromolecules, understanding RNA structure and folding and assessing drug responses at the molecular, cellular, organismal and population levels. Altman believes that it is critical to bring awareness to the greater scientific community that computational biologists and bioinformaticians are more than just great collaborators, but they also lead major research projects. He considers service to ISCB as a way established principal investigators, junior faculty, and trainees can help bring about this awareness to advance the field. Altman considers ISCB to be a community that provides both valuable service opportunities and sources of mentorship and collaboration for scientists. Altman’s dedication to the field computational biology has been recognized by his election as an ISCB Fellow (2010), as well as with numerous other honors, including election as a member of the National Academy of Medicine (formerly the Institute of Medicine, 2009) and a Fellow of the American Association for the Advancement of Science (2014). Altman has also worked as an editor and reviewer for numerous scientific journals, including serving as Co-Editor-in-Chief of the Annual Review of Biomedical Data Science. Altman’s many years of service to ISCB have been critical to the very formation and evolution of the Society from its infancy as a small meeting to the globally recognized professional organization that it is today.

The ISCB Innovator Award recognizes an ISCB scientist who is within two decades of having completed his or her graduate degree and has consistently made outstanding contributions to the field of computational biology. The 2018 winner is Dr. M. Madan Babu, Programme Leader at the MRC Laboratory of Molecular Biology, Cambridge, UK. Madan will receive his award and deliver a keynote presentation at the 2018 International Conference on Intelligent Systems for Molecular Biology in Chicago, Illinois being held on July 6–10, 2018. M. Madan Babu is the head of the Regulatory Genomics and Systems Biology group at the MRC Laboratory of Molecular Biology, Cambridge, UK. His work focuses on understanding how cellular systems are regulated at different scales (molecular, systems and genomic levels) and how this impacts genome evolution. Madan grew up in Chennai, India and developed early interests in computer science and biotechnology. As a young child, he has vivid memories of his father bringing home a personal computer and soon after he became interested in learning to program. He also remembers when his family first started using the internet, and recalled, ‘In the mid-90’s, we started having access to the Internet. This made a big difference in the days where access to information beyond textbooks was not readily available; so thanks to my father I had these opportunities early in my life’. Madan discovered biotechnology as a high school student, and attributes his lifelong interest in biology to the impact of his biology teacher, Dr. M.C. Aruna, who discussed foundational biological concepts with him, including how genetic information can be used to understand living systems. Madan went on to pursue a Bachelor of Technology (Biotechnology) degree at Anna University, Center for Biotechnology in Chennai, India. He first became of aware of computational biology during year undergraduate research internship, at which time he was exposed to the work of Cyrus Chothia and Arthur Lesk in a course on protein structure. He became fascinated with this research area and then delved into seminal papers on computational genomics, protein engineering and structural bioinformatics. As an intern, Madan pursued undergraduate research under the guidance of Prof. Balaram and Prof. K. Sankran, and saw this key turning point in his career path. He recollected, ‘We started applying methods from computer science to study protein sequences and structures. For the first time, I experienced how to define a scientific problem, develop computational methods to solve it and write up and defend the findings for publication. This really got me excited and that was when I decided that I would like to pursue a career in computational biology’. Madan recognizes that his interest in computational biology was fostered by his ability to access publicly-available protein and genomic data on his own computer, as well as the open access he had to lecture materials, methods and algorithms from computational biologists spanning the globe. He said, ‘I cannot forget the day when I wrote an email to RCSB from India and received a five-part CD-ROM with co-ordinate data for all protein structures. Being able to look at protein structures using RASMOL from home and writing FORTRAN programs to analyze structures as an undergraduate student was one of the most exciting experiences that really captured my interest in the field’. Madan left India in 2001 to pursue his PhD in computational genomics at the MRC Laboratory of Molecular Biology and Trinity College, University of Cambridge, UK under the guidance of Dr. Sarah Teichmann. His PhD research explored various aspects of gene regulatory networks, and marked the beginning of a very fruitful mentorship under Teichmann. Madan carried out his post-doctoral training at the National Center for Biotechnology Information, NIH in Bethesda, MD, USA under the guidance of Dr. L. Aravind, during which time he learned the importance of having broad interests in diverse subject areas as well as critically analyzing the complexity of biological systems at every possible level of detail. After a brief but extremely productive post-doctoral fellowship, Madan became a group leader at the age of 26 of the Regulatory Genomics and Systems Biology Group at the MRC Laboratory of Molecular Biology in 2006. As a PI, he has come to appreciate how his team of scientists can work together to tackle scientific questions on a much larger scale and shed new light on long-standing, fundamental questions. He said, ‘One of the things that I really enjoy about the field of computational biology is that you really integrate knowledge from various disciplines––biology, statistics, computer science, mathematics, physics and chemistry. This means our lab is an amalgamation of people across disciplines that are really passionate about using interdisciplinary approaches to solve the problems they are working on’. Madan’s group currently focuses on several areas of research, including studies on G-protein coupled receptors, a protein family involved in almost every aspect of human physiology and targeted by numerous drugs. Madan’s group is also using a combination of computational and experimental approaches to discover which parts of unstructured protein regions are functional and understand what makes them functional. His group is interested in applying developments in statistical learning and advances in large-scale genome sequencing to better understand natural variation in the human population as well as gain insight into how genomic variation impact rare and common diseases. Madan is greatly honored to be selected as the recipient of the 2018 ISCB Innovator Award. He is grateful for his academic mentors and colleagues, including Sarah Teichmann, L. Avarind, Cyrus Chothia, Michael Levitt, Veronica Van Heyningen, Eugene Koonin, Stephen Michnick, Richard Kriwacki, Uri Alon, Gebhard Schertler, Peter Wright, Keith Dunker, Janet Thornton, Tom Blundell and Venki Ramakrishnan, who have inspired him through their work and/or provided him valuable advice at various stages of his career. He is also appreciative of his past and present group members, and the MRC Laboratory of Molecular Biology for the freedom to develop new skills and take risks in pursuing research that pushes scientific boundaries. Conflict of Interest: C.N. Fogg was paid to write this article.

Altman's years of dedicated service to ISCB began when he attended the very first ISMB meeting in 1993.As a brand new faculty member, he remembered how he felt at home at ISMB, surrounded by a community of scientists also interested in computational biology and bioinformatics.Altman's enthusiasm at this first ISMB meeting led him to help organize the next ISMB meeting.He recalled, "It became clear that there was no obvious 'host' for ISMB 1994, so I volunteered to host it at Stanford, where we had a lovely meeting with a couple of hundred people.We had some extra money after paying our bills, so we wanted to send the money to wherever ISMB 1995 was going to be (UK).For the first few years, this is how ISMB worked-the organizers from one year would send the leftover funds as a seed for the next ISMB.There was no organization, and as the size of the leftover check increased, we started getting nervous and realized we needed to create a legal entity."ISCB was born at ISMB 1997 in Halkidiki, Greece, where organizers of former ISMB meetings and others sat at dinner on the beach and planned the society and figured out how to incorporate it.Altman has warm recollections of that historic gathering and said, "There are pictures of that great dinner and group, and I treasure the memory of that meeting".Altman has enjoyed serving ISCB at all levels since its inception, from work on the Publications Committee and as a conference organizer to his tenure on the ISCB Board of Directors (

In search of biological significanceRuth Nussinov (Fig 1) is a computational biologist with research interests that have touched every aspect of the field, from her PhD research on RNA secondary structure prediction to her visionary work on DNA sequence analysis, to proposing that all protein (and other biomacromolecules) conformations preexist and that all dynamic proteins are allosteric, to her current studies focused on Ras signaling in cancer.Nussinov's deep intellectual curiosity has guided her research interests throughout her career.Nussinov was raised in Rehovot, Israel, and attributes her early interest in science to watching her father conduct pioneering agricultural research that focused on adapting crops to the Israeli climate [1,2].Nussinov's father, Shmuel Hurwitz, was born in Minsk, Russia, and studied chemistry at Moscow University but later immigrated to Palestine (present-day Israel) after his arrest for Zionist activities.

DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

The International Society of Computational Biology and Bioinformatics (ISCB) brings together scientists from a wide range of disciplines, including biology, medicine, computer science, mathematics and statistics.Practitioners in these fields are constantly dealing with information in visual form: from microscope images and photographs of gels to scatter plots, network graphs and phylogenetic trees, structural formulae and protein models to flow diagrams, visual aids for problem-solving are omnipresent.The ISCB Art in Science Competition 2017 at the ISCB/ECCB 2017 conference in Prague offered a way to show the beauty of science in art form.Past artworks in this annual exhibition at ISMB combined outstanding beauty and aesthetics with deep insight that perfectly validated the exhibit's approach or went beyond the problem's solution.Others were surprising and inspiring through the transition from science to art, opening eyes and minds to reflect on the work being undertaken.Thirty unique pieces were showcased in the Art in Science competition at ISCB/ECCB 2017 in Prague.There winners (reproduced below) were selected by the Art in Science review committee (Figs 123).

2017 marks the second year of the ISCB Innovator Award, which recognizes an ISCB scientist who is within two decades of having completed his or her graduate degree and has consistently made outstanding contributions to the field. The 2017 winner is Dr. Aviv Regev, Professor of Biology at the Massachusetts Institute of Technology (MIT), a Core Member and Chair of the Faculty of the Broad Institute of MIT and Harvard, and an HHMI Investigator. Regev will receive her award and deliver a keynote address during ISMB/ECCB 2017 in Prague, Czech Republic (July 21–July 25, 2017). Aviv Regev first pursued her studies in a unique interdisciplinary program at Tel Aviv University, where she planned to focus on math and computer science (https://www.hhmi.org/scientists/aviv-regev). But she discovered her interest in biology in the classroom of evolutionary biologist Eva Jablonka. Regev said, ‘I found biology because of her—in my first year as an undergrad, I took a genetics course with her in what is now called the ‘flipped classroom’ style. It was all abstract and inferential, and I was hooked’. Before starting her PhD thesis at Tel Aviv University, Regev began to really think about cells as computers, particularly how they are comprised of circuits. Regev’s deep interest in this concept started at a conference where new approaches for modeling concurrent computation were featured, and she immediately considered this as a way to model cell circuitry. She was able to develop her ideas into a PhD project under the mentorship of Udi Shapiro and Eva Jablonka, and she recalled, ‘No one was working on this type of project. I did, however, have the great fortune to find Udi, who listened to my idea. He thought it was important. He didn’t want to work on it himself—but he wanted me to be able to work on it’. Regev completed her PhD in 2002 and was selected to be a Bauer Fellow at the Center for Genomics Research at Harvard University, which gave her an intellectual community, as well as freedom and funding to build a small independent research group. She continued to pursue her interest in modeling cell circuits using gene expression and genomic data, and she developed with her colleagues several widely used algorithms and computational tools, including Module Networks and Synergy. She received early support from Andrew Murray at Harvard University, who shared Regev’s view that it was critical to deeply understand both theory and experiments. In 2006, Regev was given a joint faculty appointment at MIT and the Broad Institute, and she started applying her cell circuit modeling algorithms to understanding different cell types, particularly cells of the immune system. Once again, Regev struck out on an independent line of research. She recalled, ‘Many people were not focused on circuits. But that was OK. I wanted to build and be part of a community that would open a new direction’. Eric Lander at Broad—a longtime supporter of female and young scientists with leadership potential—stood behind and supported Regev’s independent scientific vision at this critical point in her career. Regev’s independent research program has blossomed since she founded her lab, and she has applied her interest in how cellular circuits function and rewire to a wide range of biological questions, including how immune cells rapidly respond and differentiate, how hematopoietic stem cells develop into different blood cells and how evolutionary changes occur over millions of years. She is both a computational biologist with keen instincts about how to extract insight from data, and an experimental biologist with the ability to create new methods and deploy cutting edge technology to address fundamental questions. Regev continues to be drawn to seemingly intractable problems, such as biological scenarios with a massive number of hypothetical combinations or interactions, and making them into manageable problems by using sampling approaches. Her work on cells of the immune system reflects this focus, and she recalls one of her most unexpected findings emerged in 2012 while working with collaborators on applying single-cell RNA-seq to the analysis of dendritic cells. In contrast to present day technology, which enables the profiling of thousands of cells quickly and cheaply, this study only looked at 18 cells and required a tremendous effort. Regev recalled, ‘What we found was surprising in two ways. First, we were examining just one cell type which we thought was well-defined, so we did not expect to find major differences in gene expression between the cells—yet we saw 1000-fold differences, from which we could recover regulatory molecules that accounted for this variation. Second, we discovered surprising patterns in alternative splicing—some cells preferentially used one isoform, others used another. We had been expecting the cells to use both. This added up to a bigger surprise: we weren’t really looking at one group of cells. We were looking at two subgroups, which we now know represent different developmental programs. A great deal of my work now focuses on understanding heterogeneity of this type—defining and understanding cells at a much higher resolution than we could before’. Regev has passed along her love of science through her mentorship of postdocs, graduate students, and undergraduates, and outside of the lab she has maintained an intense teaching load and worked to overhaul the undergraduate genetics course to include quantitative content. She is grateful to her mentors who gave her freedom to pursue her own scientific interests and this has guided her style of mentorship. She said, ‘Today, when I see a person with an idea, I don’t care about career stage—maybe they’re a grad student or an undergrad; maybe they are a seasoned staff scientist. I care about who they are. Do they show the seeds of independence, vision and leadership? And what is their idea? If it’s challenging in entirely new ways, and can transform the world, it should be grown. As I mentor my students and postdocs, I try to let them spread their own wings—to be their colleague and collaborator’. At Broad, Regev was recently appointed Chair of the Faculty, and in this role she has been focusing on initiatives to strengthen and build communities around computational biology and advance software engineering approaches to biological data analysis. She has served the greater computational biology community in many ways through work on numerous advisory boards, journal editorial boards and program committees for conferences. Regev has been a reviewing editor for eLife since its inception, and more recently a senior editor with a major responsibility for computational biology, genomics and theory papers. Regev is gratified by her selection for the 2017 ISCB Innovator Award, and she said, ‘Biology is such a data science now, and ISCB is the community that made that happen—so it is especially exciting and gratifying to be receiving such an honor from peers in this community’.

computational biology and bioinformatics through their research, service and education work.

The International Society for Computational Biology (ISCB) each year recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, an admired computational biologist and founding ISCB Board member. Winners of the Overton Prize are independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching and service. ISCB is pleased to recognize Dr. Christoph Bock, Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, Austria, as the 2017 winner of the Overton Prize. Bock will be presenting a keynote presentation at the 2017 International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Prague, Czech Republic, being held during July 21–25, 2017. Christoph Bock’s scientific curiosity was nurtured from a young age. His parents were math and science teachers, and while they did not push him to pursue these areas of study, he sees how this intellectually stimulating environment cultivated his natural curiosity and provided a critical foundation to his career as a scientist. Bock started exploring computer programming from the age of 12, and he realizes in retrospect how learning to code was a valuable tool for practicing problem solving and scientific thinking. During high school, Bock specialized in physics and math. His undergraduate studies at the University of Mannheim focused on computer science and business information systems, emphasizing machine learning and artificial intelligence. Toward the end of his studies, Bock yearned to tackle questions with broader relevance than the ‘toy problems’ he encountered in his course work. Bock recalled, ‘Human biology seemed the biggest challenge and also most societally relevant. I was lucky that Jürgen Hesser offered a bioinformatics lecture and agreed to supervise my Master’s thesis at the University of Mannheim’. His Master’s research work focused on protein structure prediction and homology modeling. Bock pursued his PhD studies in bioinformatics under the supervision of Thomas Lengauer at the Max Planck Institute for Informatics, studying epigenetic regulation of the genome. ‘Moving into bioinformatics and epigenetics, I had to catch up on a lot of important biological knowledge’, Bock recalled. ‘Reading papers and collaborating was key, but it also helped that my research focused on a field that was quite young, with ample opportunity to try out something new’. He attributes much of his bioinformatics training to the time spent in the research group of Thomas Lengauer, and he has been grateful for his mentor’s continued support and collaboration throughout his early career. Bock also acknowledges the important guidance and feedback on his research provided by Jörn Walter, who co-supervised his PhD dissertation and introduced Bock to the international epigenetics community. Bock’s first encounter with epigenetics data transformed his scientific career path, and he has been one of the first bioinformaticians that dedicated their work to epigenetic data. ‘When I started my PhD studies in 2004, the largest epigenetic dataset consisted of just over 100 data points, and one of my first papers established epigenome prediction as a means of inferring what was still very difficult and costly to measure experimentally’. In the following years, next-generation sequencing transformed the field, and it became possible to collect several billion data points in a single epigenome mapping experiment. This development created a strong demand for bioinformatic methods. ‘Working at the forefront of the epigenome revolution has been the highlight of my scientific research so far. But the most exciting times may still be ahead as epigenome research is starting to become broadly relevant for medicine, and I am looking forward to contributing to this development’. Bock developed several software tools as part of his PhD, including BiQ Analyzer for processing DNA methylation data and EpiGRAPH for analyzing and predicting epigenome profiles in their genomic context. Bock went on to pursue postdoctoral studies under Alexander Meissner at the Broad Institute. There, Bock was exposed to the world of wet-lab biology, and he discovered the thrill and power of jointly developing new laboratory techniques and computational methods, which he used to study the epigenome of pluripotent and hematopoietic stem cells. In 2012, Bock started his own research group at CeMM, an institute dedicated to advancing precision medicine through basic and translational research. He was hired by Giulio Superti-Furga, Scientific Director of CeMM, who, as Bock said, ‘Provided ample encouragement and let me try things that were initially quite far outside of my comfort zone, such as starting a wet lab and leading a next generation sequencing technology platform’. Bock has thrived at CeMM, where he has been able to work with many passionate researchers within the institute and at the neighboring Medical University of Vienna. At CeMM, Bock has also developed his personal style of being a PI and mentor, acting as a catalyst of ideas and projects for an interdisciplinary team. He explained, ‘Our lab combines computational and wet-lab biology on roughly equal terms, with a good dose of technology development – including single-cell sequencing, CRISPR, epigenome editing, machine learning, and more. There is also an extensive network of collaborations, ranging from fundamental biology to immediate clinical applications in the area of personalized and precision medicine. It is a great privilege to work with such an interdisciplinary and creative group of smart people’. Bock considers the success of his students and postdocs as a key measure of his achievement as a PI. He explained, ‘I work hard to maintain an environment in which every group member can build a great CV and learns what he or she needs to advance in their scientific career. So far, we have a 100% success rate of postdocs moving on to attractive PI jobs, which is great for young lab. But it is clear that helping others succeed in their career is not an easy task, and you need to create room for success and failure, and a safety net that encourages risk taking’. Bock is still excited about epigenetics and what it can teach us about a cell’s past, present and future. He hopes that epigenomic data can be used to understand the regulatory logic of cells and to determine what goes awry in diseases like cancer. Bock said, ‘We are pursuing an engineering-inspired "build it to understand it" approach to cancer biology, where we combine CRISPR epigenome editing and computationally designed drug combinations to rationally reprogram normal cells into cancer cells and vice versa. Building upon a breakthrough technology for pooled CRISPR screening with single-cell sequencing, We seek to decipher complex biological pathways and gene regulatory networks in high throughput, in order to overcome the classical "one gene, one postdoc" paradigm of functional (epi-)genomics’. Bock is deeply gratified to be honored with the Overton Prize, especially since he will receive his award this year in Prague. He said, ‘Ten years ago, I attended ISMB 2007 in Vienna – one of the first conferences where I presented my PhD project on epigenome prediction. That year, Eran Segal won the Overton Prize, and his keynote lecture about DNA’s regulatory code reinforced my interest in understanding the role of epigenome regulation in biology and medicine. ISMB 2007 was also my first time in Vienna, and the great impressions from that visit surely contributed to the fact that a job ad from Vienna caught my attention a few years later. This year, it will be my pleasure to give the Overton Prize lecture at ISMB 2017 in Prague, ten years and just a few hundred kilometers away from a truly career-defining ISMB 2007’.

The Outstanding Contributions to ISCB Award was launched in 2015 to recognize individuals who have made lasting and valuable contributions to the Society through their leadership, service, and educational work, or a combination of these areas. Fran Lewitter is the 2017 winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2017 Intelligent Systems for Molecular Biology (ISMB)/European Conference on Computational Biology meeting in Prague, Czech Republic being held from July 21 to 25, 2017. Fran Lewitter completed her PhD in Human Genetics and Statistical Genetics at the University of Colorado Boulder. After completing postdoctoral work in Genetic Epidemiology at Harvard Medical School, she worked on the first 5 years of the GenBank project. Lewitter then worked in the Biology Department at Brandeis University in a number of capacities, including supporting molecular biology computing and being involved with their Genetic Counseling program. In 1994, she joined the Whitehead Institute for Biomedical Research in Cambridge, MA, to run a bioinformatics core facility. For 20 years, she worked with and trained basic biomedical researchers who were doing sequencing or were using bioinformatics to gain a deeper understanding of different biological questions. She was later named the Founding Director of Bioinformatics and Research Computing and was given a larger staff as the demand for bioinformatics information grew in the late 1990s and early 2000s. Lewitter’s first encounter with ISCB occurred when she attended ISMB 2001 in Copenhagen, Denmark, followed by a 1-day satellite meeting, Workshop on Education in Bioinformatics (WEB). At the time, Whitehead did not have a large bioinformatics community, and she was in search of peers who were running bioinformatics core facilities and teaching bioinformatics to biologists. ‘One thing that attracted me to go [to ISMB] was the one day workshop on education and bioinformatics, since I was so heavily involved in educating people. I went to every meeting since then’. At ISMB 2002 in Edmonton, Lewitter helped organize an informal gathering of bioinformatics core facility managers, and this unique gathering spurred the organization of a mailing list, which became an invaluable resource for Lewitter and her peers as they faced challenges and questions unique to running a core facility. Since her early encounters with ISCB, Lewitter has become a tireless advocate for bioinformatics education and training on behalf of ISCB. As a core facility director, she has offered her unique academic perspective and voice through her service on the ISCB Education Committee and as a member of the Board from 2008 to 2017. Lewitter recognized the growing demand for bioinformatics training early in her involvement with ISCB, and she worked to strengthen ISCB’s role in supporting bioinformatics education and training by promoting the inclusion of bioinformatics education content in the main conference programs. To this end, she has organized Workshops on Education in Bioinformatics (WEB) at ISMB meetings since 2009, and she has helped build ISCB community activities including the CoBE COSI (Computational Biology Education Community of Special Interest). Lewitter’s leadership of the ISCB Education Committee helped unite the global bioinformatics education community through shared objectives and brought greater awareness of the committee’s work through tutorials and training opportunities offered at ISCB conferences. Lewitter recognizes that one of the most critical aspects of training is ‘to introduce biologists to bioinformatics vocabulary whether or not they would be using the primary bioinformatics tools’. This fosters better collaborations between bioinformatics experts and bench scientists and is necessary to facilitate the ongoing integration of bioinformatics into all aspects of biology. Lewitter has been instrumental in bringing together ISCB and GOBLET (the Global Organization for Bioinformatics Learning, Education and Training) and coordinating activities by which these two organizations work together to further bioinformatics training on a global scale. She has advocated for the development and maintenance of bioinformatics education resources on ISCB webpages, and these electronic resources are valuable tools used by the global bioinformatics education community. Lewitter has valued her membership in ISCB for providing her opportunities to ‘get to know innovative people’. She has especially appreciated meeting other core facility directors and managers. Lewitter said, ‘It’s gratifying to hear I am doing the right thing, or other people have ideas that can help me or I can help them. It is good to talk to other people about issues of running a core facility, what courses to teach or what tools are the best to teach?’ Despite having retired from Whitehead Institute 3 years ago, she enjoys her continued involvement in ISCB activities. She is also heartened by the rising generation of ISCB members who are involved with the ISCB Student Council. Lewitter hopes ISCB will continue to grow and thrive and is grateful for being recognized for her steadfast efforts to promote and further bioinformatics education.

selected Pevzner as the 2017 winner.Pevzner will receive his award and deliver a keynote address at the 2017 Intelligent Systems for Molecular Biology-European Conference on Computational Biology joint meeting (ISMB/ECCB 2017) held in Prague, Czech Republic, from July 21-25, 2017.ISMB/ECCB is a biennial joint meeting that brings together leading scientists in computational biology and bioinformatics from around the globe.

The Outstanding Contributions to ISCB Award was launched in 2015 to recognize individuals who have made lasting and valuable contributions to the society through their leadership, service, and educational work or a combination of these areas.Fran Lewitter is the 2017 winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2017 Intelligent Systems for Molecular Biology (ISMB)/European Conference on Computational Biology meeting in Prague, Czech Republic, which will be held from July 21-25, 2017.Fran Lewitter (Fig 1) completed her PhD in human genetics and statistical genetics at the University of Colorado Boulder.After completing postdoctoral work in genetic epidemiology at Harvard Medical School, she worked on the first 5 years of the GenBank project.Lewitter then worked in the biology department at Brandeis University in a number of capacities, including supporting molecular biology computing and being involved with their genetic counseling program.In 1994, she joined the Whitehead Institute for Biomedical Research in Cambridge, Massachusetts, to run a bioinformatics core facility.For 20 years, she worked with and trained basic biomedical researchers who were doing sequencing or were using bioinformatics to gain a deeper understanding of different biological questions.She was later named the Founding Director of Bioinformatics and Research Computing and was given a larger staff as the demand for bioinformatics information grew in the late 1990s and early 2000s.Lewitter's first encounter with ISCB occurred when she attended ISMB 2001 in Copenhagen, Denmark, followed by a one-day satellite meeting, Workshop on Education in Bioinformatics (WEB).At the time, Whitehead did not have a large bioinformatics community, and she was in search of peers who were running bioinformatics core facilities and teaching bioinformatics to biologists."One thing that attracted me to go [to ISMB] was the one-day

The International Society for Computational Biology (ISCB) each year recognizes the achievements of an early-to mid-career scientist with the Overton Prize.This prize honors the untimely death of Dr. G. Christian Overton, an admired computational biologist and founding ISCB board member.Winners of the Overton Prize are independent investigators

Aviv Regev: Seeing cells as life's smallest circuitsAviv Regev (Fig 1) first pursued her studies in a unique interdisciplinary program at Tel Aviv University, where she planned to focus on math and computer science (https://www.hhmi. org/scientists/aviv-regev).However, she discovered her interest in biology in the classroom of evolutionary biologist Eva Jablonka.Regev said, "I found biology because of her-in my first year as an undergrad, I took a genetics course with her in what is now called the 'flipped classroom' style.It was all abstract and inferential, and I was hooked."Before starting her

The International Society for Computational Biology (ISCB) recognizes an established scientist each year with the Accomplishment by a Senior Scientist Award for the significant contributions he or she has made to the field. This award is bestowed to scientists who have contributed to the advancement of computational biology and bioinformatics through their research, service and education work. Professor Søren Brunak of the Novo Nordisk Foundation Center for Protein Research in Copenhagen, Denmark has been selected as the winner of the 2016 Accomplishment by a Senior Scientist Award. The ISCB awards committee, chaired by Dr Bonnie Berger of the Massachusetts Institute of Technology in the USA, selected Brunak as the 2016 winner. Brunak will receive this award and deliver a keynote address at the 2016 Intelligent Systems for Molecular Biology meeting (ISMB 2016) being held in Orlando, Florida on July 8–12, 2016. ISMB is ISCB’s world class annual meeting that brings together computational biologists and interdisciplinary scientists from around the globe. Brunak’s early interest in physics began with a childhood friendship with Jakob Bohr, grandson of Nobel Laureate physicist Niels Bohr. He considers this early informal exposure to physics instrumental in developing his interest in the field but acknowledges that his physics teacher in primary school also nurtured his interest. Brunak said, ‘I was primed by the fact that one of my childhood friends was Jakob Bohr. I grew up close to this family. Maybe I was therefore listening a little more to what the physics teacher would come up with. He was good at turning deep questions into something that could be understood by kids our age’. Brunak went on to study physics formally as a graduate student but first took a detour in astronomy. He recalled, ‘First I went into astronomy, but I found it increasingly difficult to explain at dinner parties the importance of astronomy’. He then completed his Master of Science in physics in 1987 at the Niels Bohr Institute, University of Copenhagen. ‘I had been fascinated by computers. My masters thesis was titled The Physics of Computation (in Danish ‘Computerens Fysik’), and I studied what happens in the computer when it computes. I was inspired by the work of Rolf Landauer and Charles Bennett at IBM. They worked on determining if you could compute without dissipating heat in reversible physical processes where no information would be discarded’. It was Brunak’s interest in the work of Bennett that stimulated his interest in biology. ‘Bennett used DNA transcription as an example of how a computation (a copy operation) can be done without dissipating a lot of energy. My thesis was also about computation processes in the brain, which are related to machine learning. It’s also about throwing information away so what you are after is distilled out of the data. In the big data context, there is a huge information reduction need so my experience with the physics of computation has inspired me when designing machine learning algorithms that use a lot of information and end up with a yes or no, for example answering the question of whether a protein structure is helical or not at a given position in the amino acid sequence. A lot of bioinformatics is about throwing information away in a smart way so what you are really after is retained’. Brunak completed his Ph.D. in computational biology in 1991 in the Department of Structural Properties of Materials at the Technical University of Denmark. He then went on in 1993 to become founder and director of the Center for Biological Sequence Analysis at the Technical University of Denmark, a large center that still exists. His early work in bioinformatics focused on protein structure. He recalled, ‘I worked with protein structure with machine learning approaches. Meetings were small, data sets were small. We tried to get a lot out of little. We were raised in the data-poor era. The machine learning approach is not only good for boiling down but also for extracting’. Even during this era of limited data, Brunak considered computer power an important priority. ‘During my early studies in the late 1970s I started with punch cards and huge magnetic tapes. During my PhD I obtained a grant for a fast four processor Apollo 10000 machine, and I later always spent a lot of money on supercomputers so computer speed was not a problem. Now it is a real problem because we have millions of instances of a genome. We are in a situation where computer science matters in a new way. I have been around computers so long so I’ve seen a lot of special purpose hardware developed. But people always go back again and again to the general purpose computer that can take any algorithm, or do things like align sequences with any setting’. Brunak’s early bioinformatics studies looked at both structure and function and were not limited to sequence properties. Machine learning was integral to these studies, and he went on to write an authoritative text on the subject with Pierre Baldi in 1998, titled Bioinformatics: A Machine Learning Approach. Brunak developed several widely used algorithms rooted in machine learning including NetGene, which predicted introns and exons and splice sites, and SignalP, a signal peptide predictor. He recounted, ‘This was the time of the genome project, so we started doing exon and intron and splice site prediction using this method called NetGene. Both SignalP and NetGene were interesting in that they integrated several different predictors and exploited the same data from different angles. With NetGene, we had a splice site predictor and an exon predictor and we put them together and we got a much better algorithm out of it than staying just in just the splice site or coding/non-coding domain. In SignalP we also used the same data in two different ways’. Brunak recalls some of the surprises of his early research. ‘My first Nature paper was a small paper in 1990. It was a paper where we predicted splice sites using machine learning with neural networks. We noticed a group of splice sites that the network really did not want to learn. We just kept training it and it still would not learn them. We started looking at them and it turned out that half of them were database errors, and the other half were more interesting, they were errors made by experimentalists when they interpreted their [sequence] gels. They had put the splice site in the wrong place. The would learn the rare, but true GC donor sites very late, but still learn them. It was an interesting paper that showed the power of machine learning–that it could be a little more clever than the quality of the data. Nature was getting tough on GenBank for removing errors, and here was a computational approach for cleaning up data sets. We used the same technique with SignalP to identify likely errors. [We thought] either it’s an error or super unusual and therefore interesting. We could see in some databases, with signal peptides, that 10–15% of the data was wrong’. Brunak saw this tedious work as an important contribution to cleaning up data sets and spent several years on this effort. During the Human Genome Project era, Brunak recognized with many others in the field the limits of gene prediction from sequence information alone. But his research using neural networks alluded to some of our present day understanding of the complexities of genomes. Brunak said, ‘It’s not surprising now that gene prediction was not 100% successful. Now we know that there’s transcription everywhere and that what constitutes a gene is highly complex. In 1992, we had a paper in The Journal of Molecular Biology (JMB) examining the ways how a neural network looks for gene features in order to produce a prediction. It turned out when we predicted introns and exons, it looked for a specific GC-rich signal. It was not easy to get a paper accepted into JMB, especially when you were trying to deconvolute theoretically neural network parameters into some biological signal. The pattern it looked for was perhaps known to a referee as an early example of an enhancer. Part of the reason of the success of the machine learning approach is that we didn’t need to know upfront the features that were behind biological mechanisms’. Brunak’s research focus has shifted direction in recent years during this era of large scale genome projects. In 2007, he was a co-founder of the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen. The Center’s main goal is to look for proteins of therapeutic value, and they are developing approaches that fit into a healthcare context. Brunak leads the translational disease systems biology group, which looks at genome, proteome and health data, where some cover the entire Danish population. Brunak explained, ‘I am interested in disease trajectories, the order in which you get diseases, comorbidities and follow-on diseases. If you get type 2 diabetes, you won’t get the same complications as your neighbor. There are certain trajectories that are more probable than others’. For the entire Danish population, almost all personal information, including education, job status and health records, are tied to a Dane’s personal identification number. As such, researchers including Brunak have an abundance of unique data to work with, and much of his work has focused on boiling down this data into meaningful observations. ‘My contribution is to put patients into progression groups and interpret proteomics data. We for example group diabetics and will see how their trajectories differ. Having the ability to work from the molecular side and having health data is presumably going to be powerful. We have data from 11 million people living and dead. We also essentially have the family tree from the entire country because it’s encoded in the personal identification number’. Brunak’s enduring contributions to computational biology and bioinformatics have spanned his career, and given the scope of his recent work, he is certain to make a lasting and valuable contribution to the field.

The Outstanding Contributions to ISCB Award was launched in 2015 to recognize individuals who have made lasting and valuable contributions to the Society through their leadership, service and educational work, or a combination of these areas. Burkhard Rost is the 2016 winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2016 Intelligent Systems for Molecular Biology (ISMB) meeting in Orlando, Florida on July 8–12, 2016. Rost is the Alexander von Humboldt Professor and chair of bioinformatics and computational biology at the Technical University Munich. His research interests focus on using machine learning and artificial intelligence to predict the structures and functions of proteins and genes. Rost has served ISCB in numerous positions throughout his career, including being co-chair of the largest annual meeting in computational biology, Intelligent Systems in Molecular Biology (ISMB), during 2007 (Vienna), 2008 (Toronto), 2011 (Vienna), 2012 (Long Beach) and 2013 (Berlin). Rost served as ISCB president from 2007 to 2014. When he assumed the leadership position, the Society was in financial turmoil. He recalled, ‘All I wanted to do was clean up’, and sought out colleagues who would help steer ISCB in their right direction through their leadership roles on the Executive Committee (EC) and the Board of Directors, and as committee chairs. He attributes the flourishing of ISCB under his leadership to these colleagues and said, ‘I have found a way to motivate the people who are passionate about what they do. I can motivate people and I found the right people’. Rost strove to broaden the international reach of ISCB beyond Europe and the USA and said, ‘We wanted ISCB to have conferences in many places, outside the realm of what we typically do. I believe we found a way of making it sustainable’. During Rost’s term as president, he led the effort to organize several international meetings in Africa, Asia and Latin America. These truly international meetings included ISCB Africa (2010: Bamako, Mali; 2011: Cape Town, South Africa; 2013: Tunis, Tunisia; 2015: Dar es Salaam, Tanzania) in cooperation with the African Society for Computational Biology and Bioinformatics (ASBCB), ISCB Latin America (2010: Montevideo, Uruguay; 2012: Santiago de Chile, Chile; 2014: Belo Horizonte, Brazil), and most recently ISCB Asia (2011: Kuala Lumpur, Malaysia; 2012: Shen Zhen, China; 2013: Seoul, South Korea). ISCB continues to organize these international meetings and is developing other virtual platforms, like ISCBconnect, to help ISCB members from around the globe connect with each other outside the confines of a conference. Rost wanted to find ways for students and trainees to become involved with ISCB in a meaningful way and helped advocate for and support the ISCB Student Council (ISCB SC). The ISCB SC has blossomed since its inception in 2004, and student members organize and manage the SC’s year round activities including scientific events, networking opportunities, soft-skills training, educational resources and career advice. The ISCB SC hosts a popular annual symposium at ISMB and has become the voice of the rising generation of computational biologists. Rost said, ‘Young people see ISCB as a society that does something and they are more active than ever before’. Rost was concerned about the lack of diversity in ISCB’s leadership at the beginning of his term and focused on getting more women on the EC because he believed diversity is essential for the success of ‘how important decisions are made’. Now women hold many leadership roles across ISCB and are being honored in growing numbers for the scientific contributions to computational biology through ISCB awards and recognition as ISCB Fellows. Rost will be remembered as one of ISCB’s most devoted presidents through his tireless service to connect the international computational biology community through multiple platforms and being a strong united voice for a very broad field. He will continue to support the ISCB community as a past-president and lifetime ISCB member.

DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone.

2016 marks the awarding of the inaugural ISCB Innovator Award, which honors an ISCB scientist who is within two decades of receiving a graduate degree, has consistently made outstanding contributions to the field, and continues to forge new directions.The inaugural winner is Dr. Serafim Batzoglou (Fig 1

The 23rd Annual International Conference on Intelligent Systems for Molecular Biology and the 14th European Conference on Computational Biology (ISMB/ECCB 2015) is shaping up to be a phenomenal meeting with world-renowned keynote speakers and changes in the conference format that aim to make for a more streamlined and user-friendly conference. The joint ISMB/ECCB conference is held biennially and is the flagship meeting of the International Society for Computational Biology (ISCB). The meeting will take place at the Convention Center Dublin, Ireland from July 10–14, 2015 and will bring together scientists from across the globe working in a broad range of computational biology-related disciplines including genomics, structural biology, proteomics, data mining, machine learning and systems biology. In the past, presentations at the meeting have been organized according to tracks: Proceedings, Highlights and Late Breaking Research tracks. Combined with the multiple track presentation, this caused frustration for attendees when choosing which sessions to attend. In 2015 all oral presentations will be presented in broad theme areas. As in the past, submissions accepted into the highly selective Proceedings track will be published in a special ISMB/ECCB Proceedings issue of Bioinformatics . Conference co-chairs Alex Bateman, Janet Kelso and Desmond Higgins and the conference committee undertook the reorganization effort and came up with five theme areas: Genes, Proteins, Systems, Disease and Data. Batemen said, ‘The idea of themes is an obvious way to organize the talks. But, selecting a small number of themes that represented all computational biology was challenging. Of course many talks will potentially fit across several themes. Time will tell whether these need any tweaking for future meetings’. Kelso believes the new organization will benefit attendees and said, ‘We hope that organizing the meeting more thematically will mean that attendees have an easier time identifying sessions that are relevant and interesting to them’. Five leading scientists have been named as theme chairs and will organize the selection of presentations from each traditional submission cateogry for each theme area. They are Yana Bromberg of Rutgers University (Disease), Janet Kelso of Max Planck Institute (Data), Nicolas Le Novere of the Babraham Institute (Systems), Martin Vingron of the Max Planck Institute for Molecular Genetics (Genes) and Ioannis Xenarios of the University of Lausanne (Proteins). As in the past, the keynote speaker line up features world-class scientists. The speakers include Amos Bairoch of the Swiss Institute of Bioinformatics (ISCB Fellows Keynote), Cyrus Chothia of the MRC Laboratory of Molecular Biology (Senior Scientist Award winner), Eileen Furlong of the European Molecular Biology Laboratory, Curtis Huttenhower of the Harvard T.H. Chan School of Public Health (Overton Prize winner), 2013 Nobel Laureate Michael Levitt of Stanford University and Kenneth Wolfe of University College Dublin. The main conference program takes place from Sunday, July 12 through Tuesday, July 14. In the tradition of previous ISMB/ECCB meetings, Special Interest Group (SIGs) and Satellite Meetings will occur prior to the conference on Thursday, July 10 and Friday, July 11. This year, the tutorials and workshops that usually precede the main meeting are being replaced by applied knowledge exchange sessions (AKES). The AKES are scheduled for Saturday, July 11 and are designed to provide interactive educational and knowledge exchange opportunities for attendees. AKES will also provide a chance for junior principle investigators to meet and exchange career advice. Six AKES have been scheduled: 3Dsig: Structural Bioinformatics & Computational Biophysics CAMDA 2015 Critical Assessment of Massive Data Analysis Automated Function Prediction (AFP-SIG) Bio-Ontologies BioVis SIG BOSC: The 16th Annual Bioinformatics Open Source Conference HitSEQ: High Throughput Sequencing Algorithms and Applications Integrative RNA Biology SIG NetBio SIG Regulatory Genomics Special Interest Group (RegGenSIG) VarI SIG AKES 01: Applied Knowledge Building networks for translation: how to use DREAM challenges and the Synapse platform as a research strategy This session will explain the rationale behind running a DREAM Challenge, the steps involved from both sides of the process (organizers and participants), the lessons learned, and the potential uses of DREAM Challenges in education. Hands-on exercises with the Synapse platform will be featured. AKES 02: Cytoscape 3 App Development: Variations on a theme—‘Hello World’ Cytoscape's real power lies in the ecosystem of community-developed apps. The most common types of apps provide access to third-party biological databases, customize data import for domain-specific data sets, and perform custom analyses and workflows. During this workshop, we will demonstrate how to develop apps for Cytoscape, targeting individuals who want to take advantage of the network visualization and analysis capabilities of Cytoscape and extend it for custom use cases. AKES 03: Bioinformatics software testing and quality assurance In this workshop, we aim to create an environment to engage bioinformatics software developers, managers of bioinformatics/genomic core facilities, researchers in reliability engineering and statisticians. We hope that cross pollination of these fields would yield interesting new insight and ideas that would open new research avenue related to bioinformatics quality assurance. AKES 04: Open-access, cloud-based, individual-level clinical trials data - sharing, dissemination and analyses In this workshop, we will discuss the reasons for data sharing and the issues surrounding it, the various ways sharing is implemented, and showcase our experience in re-analysis of clinical trials data using open immunology studies data. We will also highlight our initial work on defining a minimum information guideline for clinical trials data release. AKES 05: Using biological cyberinfrastructure to scale science and people—Applications in data storage, HPC, cloud analysisand bioinformatics training Cyberinfrastructure (CI) is a powerful enabler for data-intensive biology. Although much investigation originates in organism-centered communities there are unifying similarities across types of datasets, algorithms and overall goals. This workshop demonstrates how CI originally developed for the U.S. plant science community (via. the iPlant Collaborative project) serves all life sciences (animals, plants, microbes, etc.) by allowing communities to leverage pre-built CI solutions and develop application-specific components to a customized endpoint. AKES 06: How to navigate a bioinformatics career path Working with the ISCB student council, the Junior PI group and COBE COSI, this session is focused on career development. Here, we focus on training and preparing the bioinformatics professional to successfully launch and build a career. This session will be of interest to a wide audience. For students and junior PIs, you will participate in topics and practical sessions that can help build your career. For senior faculty and other professionals, it will provide ways in which you can improve skills to mentor your students and professionals building their career. ISMB/ECCB 2015 will also include special sessions, poster presentations in the exhibit hall, the Student Council Symposium and social activities. This year’s conference promises to be an eagerly anticipated reboot of ISMB/ECCB with great science and collaboration at its core.

2015 marks the first year that the International Society for Computational Biology (ISCB) honors one of its members with the Outstanding Contributions to ISCB Award. This award recognizes an ISCB member who has made unique and lasting contributions to ISCB through exemplary leadership, education, service, or a combination of these elements. Lawrence (Larry) Hunter, Professor at the University of Colorado Medical School, is the inaugural winner of the Outstanding Contributions to ISCB Award. He will receive this award at the 2015 Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Dublin, Ireland in July 2015. Larry Hunter pursued computational biology as a graduate student at Yale University in the 1980s before such a term for the field existed. He built a computer program that used case-based reasoning to diagnose lung tumor pathology, but he felt frustrated by the limits of computation having a noticeable impact on disease outcomes (Gibson 2012). As a freshly minted PhD with a background in artificial intelligence (AI), Hunter sought out career opportunities that would apply his skills and give him a steady paycheck. He joined the NIH’s National Library of Medicine (NLM) in March 1989 as one of its first computer scientists, during a time when NIH was trying to strengthen its influence over the Human Genome Project. Hunter began maintaining a database of AI researchers with interests in molecular biology, and in 1991 he used this list to organize the first workshop that formed the basis of the Intelligent Systems for Molecular Biology (ISMB) meeting. The official ‘first annual’ ISMB conference took place in 1993 on the NIH grounds and sold out almost instantly. Different universities in the US and UK hosted the next several ISMB conferences, and Hunter and others, including Russ Altman, Chris Rawlings, David Searls and Jude Shavlik were the primary meeting organizers. Planning and organizing each meeting presented unique challenges, but moving money for the meeting between institutions became a particularly cumbersome task. , The burgeoning popularity of the early ISMB conferences as well as the financial and logistical challenges of organizing the conferences compelled Hunter and his colleagues to consider establishing a scientific society for those who used computation to investigate biological questions. At the ISMB 1996 conference in St. Louis, MO, Hunter and members of the steering committees from prior ISMB conferences met to discuss the possibilities of organizing a new scientific society, and they voted on a board of directors, including Hunter as president, to guide this effort (Ferguson and Morrison McKay 2006). Hunter recalled, ‘I felt a great sense of obligation to make the Society work. There were a growing number of people coming to the field, and the conference was expanding pretty rapidly. I had never run an organization before, and was very concerned about getting it right. There were also some political issues that I felt I had to be very careful to get right. Researchers with a background in computational complexity theory thought of themselves as quite different from the ones who came from a background in AI. There was some discussion by people who wanted to form a different society, associated with the Research in Computational Molecular Biology (RECOMB) conference. We had a long dinner on a Greek beach at the ISMB 1997, which was the basis for working out an agreement that kept the community whole’. The board agreed on a mission statement for the nascent society at this marathon strategy session in Greece. The original statement was, ‘The International Society for Computational Biology is dedicated to advancing the scientific understanding of living systems through computation; our emphasis is on the role of computing and informatics in advancing molecular biology’, but the second phrase has been dropped to adapt to the Society’s broader focus. The board agreed on the International Society of Computational Biology as a name, and ISCB was officially incorporated as a non-profit organization in 1997.Hunter faced some unexpected challenges as president of the newly formed ISCB, including the unforeseen difficulties of trying to find a bank that would accept a large check that was the underlying funding for this organization. He was keenly aware that scientists with allegiances to ISMB or to RECOMB, a competing conference, had to feel welcome and appropriately represented by ISCB. Most surprisingly, he recalled, ‘I greatly underestimated the amount of time it would take to make it all work. We had no staff, and everything was done by the executive committee, so I put much more time into it than I thought I was going to’. He remembered how computational biology and bioinformatics were considered as peripheral and offbeat fields by many scientists at the time of ISCB’s founding. ‘Hard, logical computer science was seen as having no connection at all to wet, squishy biology’, he recounted. ‘When I mentioned “computational biology,” people couldn’t even hear the words together, they would often say “confrontational biology, what’s that?”’ ISCB has grown and evolved as a scientific society since its founding, especially as computational biology and bioinformatics have becoming increasingly vital components of biological research. He has seen ISCB become a critical resource for facilitating interactions and collaborations between scientists across fields, especially via ISMB and its other conferences. ‘I think my proudest achievement is that the society is still going today’, Hunter said. ‘I booted it up in good enough organizational and financial shape that it looks like it will have a long life. I expect it will outlive me. It’s really an honor to have created something of enduring value for so many people’. Hunter envisions that ISCB will adapt and change in the future in order to be of value to its membership. He said, ‘One interesting possibility would be for ISCB to organize events and activities to provide short-term training in informatics to biomedical researchers. Conferences like VizBi do that very well for biological visualization, and ISCB might be able to meet a need organizing similar conferences or tutorials at non-bioinformatics meetings. Twenty years from now I will be almost 75, so it will have to be the next generation to figure out how the Society evolves to stay relevant and valuable’.

UNLABELLED: The International Society for Computational Biology (ISCB; http://www.iscb.org) honors a senior scientist annually for his or her outstanding achievements with the ISCB Accomplishment by a Senior Scientist Award. This award recognizes a leader in the field of computational biology for his or her significant contributions to the community through research, service and education. Cyrus Chothia, an emeritus scientist at the Medical Research Council Laboratory of Molecular Biology and emeritus fellow of Wolfson College at Cambridge University, England, is the 2015 ISCB Accomplishment by a Senior Scientist Award winner.Chothia was selected by the Awards Committee, which is chaired by Dr Bonnie Berger of the Massachusetts Institute of Technology. He will receive his award and deliver a keynote presentation at 2015 Intelligent Systems for Molecular Biology/European Conference on Computational Biology in Dublin, Ireland, in July 2015. CONTACT: [email protected].

UNLABELLED: Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains and three-dimensional protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL). CONTACT: [email protected] or [email protected].

Computational biology has grown and matured into a discipline at the heart of biological research.In honor of the tenth anniversary of PLOS Computational Biology, Phil Bourne, Win Hide, Janet Kelso, Scott Markel, Ruth Nussinov, and Janet Thornton shared their memories of the heady beginnings of computational biology and their thoughts on the field's promising and provocative future.

The International Society for Computational Biology (ISCB) honors the achievements of an early-to mid-career scientist with the Overton Prize each year.The Overton Prize was instituted to honor the untimely loss of Dr. G. Christian Overton, a respected computational biologist and founding ISCB Board member.Winners of the Overton Prize are independent investigators in the early to middle phases of their careers who are selected because of their significant contributions to computational biology through research, teaching, and service.ISCB is pleased to recognize Dr. Curtis Huttenhower, associate professor of computational biology and bioinformatics at the Harvard T. H. Chan School of Public Health, as the 2015 winner of the Overton Prize.Huttenhower will be presenting a keynote presentation at the 2015

The 23rd Annual International Conference on Intelligent Systems for Molecular Biology and the 14th European Conference on Computational Biology (ISMB/ECCB 2015) is shaping up to be a phenomenal meeting, with world-renowned keynote speakers and changes in the meeting format that aim to make it a more streamlined and user-friendly conference.The joint ISMB/ ECCB conference is held biennially and is the flagship meeting of the International Society for Computational Biology (ISCB).The meeting will take place at the Convention Center Dublin, Ireland, from July 10-14, 2015, and will bring together scientists from across the globe working in a broad range of computational biology-related disciplines, including genomics, structural biology, proteomics, data mining, machine learning, and systems biology.Online registration is open until June 26: https://www.iscb.org/ismbeccb2015-registration.In the past, presentations at the meeting have been organized according to tracks, namely, the Proceedings, Highlights, and Late Breaking Research tracks.In 2015, all oral presentations will be presented in broad thematic areas.As in the past, submissions accepted into the highly selective Proceedings track will be published in a special ISMB/ECCB Proceedings issue of Bioinformatics.Conference co-chairs Alex Bateman, Janet Kelso, and Des Higgins and the conference committee undertook the reorganization effort and came up with five thematic areas: Genes, Proteins, Systems, Disease, and Data.Batemen said, "The idea of themes is an obvious way to organize the talks.But, selecting a small number of themes that represented all computational biology was challenging.Of course, many talks will potentially fit across several themes.Time will tell whether these need any tweaking for future meetings."Kelso believes the new organization will benefit attendees and said, "We hope that organizing the meeting more thematically will mean that attendees have an easier time identifying sessions that are relevant and interesting to them."As in the past, the keynote speaker lineup features world-class scientists.The speakers include Amos Bairoch of the Swiss Institute of Bioinformatics (ISCB Fellows Keynote), Cyrus Chothia of the Medical Research Council (MRC) Laboratory of Molecular Biology (Senior Scientist Award winner), Eileen Furlong of the

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research.As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling.Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database.Taken together, such computational efforts could significantly accelerate traditional scientific approaches.In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus.ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology [ISMB] 2016, Orlando, Florida).

The 22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) will be a world-class scientific meeting that brings together computational biologists and bioinformaticians of every career stage from diverse scientific disciplines. ISMB 2014 will convene at the John B. Hynes Memorial Convention Center in Boston, Massachusetts, on July 11–15, 2014. ISMB is the flagship conference of the International Society for Computational Biology (ISCB). This unique meeting draws scientists from a broad range of fields that use computational biology and bioinformatics, including sequence analysis, comparative genomics, proteomics, structural biology, data mining, and systems biology. ISMB 2014 is anchored by six keynote presentations from world-renowned scientists. Isaac “Zak” Kohane, the Director of the Children's Hospital Informatics Program and the Henderson Professor of Pediatrics and Health Sciences and Technology at Harvard Medical School, will be speaking on Sunday, July 13. Kohane's unique background in both pediatric endocrinology and computer science has enabled him to develop a research program that uses genomics to better understand the genetic basis of diseases, including autism and cancer. He has also developed computer systems that permit the use of information from electronic health records for genetic studies while maintaining patient privacy. Sunday, July 13, will also feature a keynote presentation by Eugene “Gene” Myers, the 2014 recipient of the ISCB Accomplishment by a Senior Scientist Award. This award honors luminaries in the fields of computational biology and bioinformatics who have made significant contributions to these areas through research, education, and service. Myers is the Director and Tschira Chair of Systems Biology at the Max Planck Institute of Molecular Biology and Genetics in Dresden, Germany. Myers is well known for his work on developing the BLAST algorithm for sequence comparison, as well as his work on using shotgun sequencing to sequence the human genome at Celera Genomics. His research is now focused on computational bioimaging. He has developed new microscopic devices and software that are used for building 3D biological models, and these tools are providing unparalleled insights into the inner workings of cells and systems. Michal Linial, a Professor of Biochemistry, Molecular Biology, and Bioinformatics at the Hebrew University of Jerusalem, Israel, will be a keynote speaker on Monday, July 14. Linial is the Director of the Sudarsky Center for Computational Biology and is the first female head of the Israel Institute for Advanced Studies. Her broad research activities encompass both “wet lab” projects and computational modeling, with particular interests in neuronal cell differentiation and synapse formation, proteomic analysis of membrane proteins, and functional genomics. The 2014 winner of the Overton Prize, Dana Pe'er, is featured as a keynote speaker on Monday, July 14, as well. The Overton Prize recognizes early- or mid-career scientists working in computational biology or bioinformatics who are rising leaders in these fields. Pe'er is an Associate Professor in the Department of Biological Sciences and Systems Biology at Columbia University. Her research focuses on understanding cellular and molecular networks at a holistic level by using computational approaches to analyze complex data sets. Robert Langer, a Professor in the Department of Chemical Engineering at the Massachusetts Institute of Technology, will give a keynote presentation on Tuesday, July 15. Langer is a prolific researcher who works on developing novel drug-delivery systems, with a particular interest in using polymers to deliver therapeutic molecules like DNA and genetically engineered proteins. Langer's innovative work was recognized most recently when he was selected as a recipient of the 2014 Breakthrough Prize in Fundamental Physics and Life Sciences. The last keynote presentation will be given on Tuesday, July 15, by Russ Altman, a Professor of Bioengineering, Genetics, and Medicine, and Computer Science. Altman has been selected as this year's ISCB Fellows Keynote Speaker. He works on building and applying new algorithms to explore diverse topics including RNA structure, how drug efficacy is impacted by genomics, and how to model motion and dynamics of biological structures. Beyond the keynote speakers, ISMB will be brimming with talks on cutting-edge discoveries across diverse areas. The Special Sessions track will run throughout the meeting and will feature hot topics that have not been featured in previous ISMB meetings. The Highlights and Proceedings tracks are also popular conference tracks that include oral presentations based on recently published papers selected through rigorous peer-review processes. The Proceedings papers are also published as an online-only open-access section of the Bioinformatics journal. The Technology track features presentations that showcase the use of novel software or hardware relevant to computational biologists. The Late Breaking Research track will also feature talks on a wide range of topics of significant interest to the bioinformatics community. A large poster session will provide an opportunity for trainees and scientists from every career stage to present their latest research findings in a collegial and collaborative atmosphere. “Birds of a Feather” sessions and workshops will be more informal sessions that encourage discussion and collaboration. These sessions will feature such themes as bioinformatics curriculum guidelines, personalized medicine, bioinformatics core facility management, trends in digital publishing, and data analysis. The exhibit hall will showcase a wide variety of organizations and companies that are developing tools and reagents relevant to computational biologists and bioinformaticians, and attendees will be able to see some of these items in action at exhibitor presentations. The ISCB Student Council will be organizing several high profile events throughout ISMB 2014. The annual Student Council Symposium will convene just prior to ISMB 2014 and will include talks by a keynote speaker and student presenters, as well as a poster session. Opportunities for career guidance and social events are also included. In addition, the ISCB Student Council will be coordinating an Art & Science Exhibition during the ISMB meeting that will feature images and videos of scientific material derived from research projects or artwork generated from scientific tools or methods. Saturday, July 12, and Sunday, July 13, will be filled with substantive one- and two-day specialized meetings that precede the main ISMB meeting. Special Interest Group (SIG) and Satellite meetings will be focused on a range of topics that include but are not limited to structural bioinformatics, mass spectrometry, and regulatory genomics. Two half-day tutorial sessions will also be held on July 12 and will feature (1) Computational Metagenomics and (2) Wikipedia: WikiProject Computational Biology. Several social events will balance out the program for ISMB 2014 and will create ample opportunities for attendees to gather together in informal settings. An opening reception is scheduled for the evening of Saturday, July 12, and poster viewing receptions are being held on both Sunday, July 13, and Monday, July 14. A World Cup viewing area will also be set up in the Exhibit Hall. As a long-standing hub of biological and computational research breakthroughs, Boston promises to be an excellent host to ISMB 2014. Both local Boston- and Cambridge-area scientists, as well as visitors from every corner of the globe, will be showcasing diverse topics that span from personalized medicine, to machine learning in systems biology, to open-source bioinformatics software development. This must-see event has something for everyone and is an excellent destination to start your next collaboration.

Myers was captivated by computer programming as a young student.He remembered his fascination being stoked by a realization and recalls, ''A computer is a programmable device, and once programmed, is a specific device for doing something that I conceived of.I found this magical.''He completed a BS in mathematics at the California Institute of Technology, but his interest in biology came during his PhD studies at the University of Colorado in the late 1970s.Myers recounted that he initially considered molecular biology as ''a source of interesting computational questions.''He was studying computer science under the guidance of his dissertation advisor, Andrzej Ehrenfeucht, who had eclectic interests that included molecular biology.Myers, along with fellow graduate students and future bioinformaticians Gary Stormo and David Haussler, was drawn by Ehrenfeucht's curiosity about such basic questions as how to compare DNA sequences and how to build evolutionary trees.

The International Society for Computational Biology (ISCB) honors the achievements of an early-or mid-career scientist with the Overton Prize each year.The Overton Prize was established in memory of Dr. G

The International Society for Computational Biology (ISCB; http://www.iscb.org) honors a scientist each year for their outstanding achievements. The ISCB Overton Prize honors an early or mid-career scientist who has already made significant and enduring contributions to the field of computational biology. Dr Goncalo Abecasis of the University of Michigan is the 2013 recipient of the Overton Prize. Dr Abecasis was selected the by ISCB's awards committee, which is chaired by Dr Alfonso Valencia of the Spanish National Cancer Research Center (CNIO) in Madrid. Dr Abecasis will receive his award and deliver keynote address at the ISCB's 21st annual Intelligent Systems for Molecular Biology (ISMB) meeting. This meeting is being held jointly with the 12th European Conference on Computational Biology and will take place in Berlin, Germany on July 21–23, 2013 (http://www.iscb.org/ismbeccb2013). Goncalo Abecasis was drawn to biology ever since he was a child. ‘From a young age, I have always been fascinated with understanding how life works’, said Abecasis. He fondly recalls spending Sundays at a bookstore with his parents and gradually collecting a small library of wildlife books. But it was his experiences in a high school computer programming club that opened his eyes to an entirely different field. ‘Although I didn't know it at the time, a key skill that later contributed to my success in genetics was my interest in computer programming’, recalled Abecasis. ‘The club was meant to keep us busy and out of trouble, but they did encourage us to try programming and pointed us in the direction of very useful techniques, like object oriented programming and the like’. Human genetics appealed to Abecasis as he pursued his undergraduate studies at the University of Leeds, and he landed a position in the laboratory of Dr Mary Anne Shaw studying ‘how genetic variation in the interleukin-1 gene cluster, a set of immune genes where variation was easy to measure with then available techniques, was related to infection by Leishmania and other tropical parasites’. This experience proved invaluable for helping Abecasis to receive funding for his PhD training in the laboratory of Dr William Cookson at the University of Oxford. Cookson's laboratory at the Wellcome Trust Center for Human Genetics at Oxford was studying genes that contribute to asthma susceptibility. In the late 1990's and early 2000's, Abecasis described this Center as ‘a mecca for human geneticists at the time, with great support from the Wellcome Trust, and lots of smart people trying new ways to run genetic studies and looking to make rapid progress in many different traits’. Abecasis also recalled that ‘as we pushed the limits of the sequencing and genotyping technologies of the time, we were soon generating datasets that were beyond the reach of existing analysis tools and methods’. Abecasis saw that, ‘It was easy to realize that new analysis methods and computer software were needed—and being in Oxford, working at the Wellcome Trust Center, was just the right place to be’. With Cookson's support, and under the co-mentorship of statistical geneticist Dr Lon Cardon, Abecasis developed software to tackle the analysis of large genetic datasets. Abecasis remembered dealing with many software bugs along the way, but then, as now, he repeated the mantra to himself that ‘all software is buggy, and this is no exception!’ Abecasis was pursuing his PhD at the same time as the race to sequence the first human genome was wrapping up. As the field of genomics was emerging, he realized that several of the methods he had developed could be used to look at how ‘individual genomes differed from this initial sequence and to understand how these differences contribute to the great diversity we see among people today’. The application of these methods to genome data also shifted his research focus away from ‘laboratory methods, technology and data generation’, and towards ‘issues related to study design and analysis’. Abecasis's unique knowledge and training in human genetics, biostatistics and computational analysis landed him a faculty position in the Biostatistics Department at the University of Michigan. Abecasis recounted the support and mentorship of Dr Michael Boehnke in the department. ‘Mike somehow convinced the Biostatistics Department at the University of Michigan to take a flutter on me, when I had just finished my PhD and had much less formal training in statistics than most of my colleagues. He has always been generous with his time, and I probably can't count the times that I have interrupted him in his office, bounced some ideas off him, and came out energized and thinking about something new to try’. Along with Boehnke, Abecasis acknowledged how fortunate he has been in the mentorship he received throughout his training, including the volunteers who taught him to code in his high school club. ‘As I knew them, I remember my mentors as demanding, generous with their time, unrelentingly positive and encouraging, and totally transparent. It is obviously a standard I'd like to meet, although I doubt I am there yet.’ Their example also motivates Abecasis to be a good mentor. ‘It is great to set a student free on an interesting open problem and have them solve it. You can do so much more with a few good trainees than you could ever accomplish on your own.’ Abecasis's research, and the field of human population genetics in general, has been transformed by the advent of high-throughput genetics. ‘We now have very clear answers about the degree and structure of genetic variation in the world today, but have also gained a lot of detail on human population history—including very ancient events, like admixture with Neanderthals’, said Abecasis. Abecasis's laboratory is now focused primarily on identifying genetic variants relevant to human disease. They look at linkage disequilibrium within human genomes to describe, ‘how groups of variants are shared among individuals’. One of the observations that Abecasis's group (and others) made several years ago, which he recalled as being surprising, was ‘that much of the genetic variation in any individual could be recovered accurately by comparing each individual with a reference set of individuals, and, more recently, we have used the process to make it relatively inexpensive to sequence large numbers of individuals. At our last count, >30 000 human genomes had been sequenced using our ‘low-coverage’ linkage disequilibrium-based approach.’ One of the highlights of Abecasis's career was being invited to the White House in 2010. ‘I was thrilled. I remember I had very short notice (perhaps a couple of days) and had to rush and find something to wear, recalled Abecasis. Although it is cheesy, it is really amazing to live in a country that functions so much like a meritocracy. I didn't have to write a check, join a committee, vote—anything. I had a good idea about how to sequence a lot of genomes more rapidly, proposed it, and not only did I get funded to try it out (it worked, by the way), but my work was selected as one of the highlights for Vice President Biden's speech on the importance of technology development and biomedical research.’ Abecasis described the importance of collaborations to his research and is a strong proponent of sharing data and software tools. ‘So many great discoveries and advances come from bringing in insights, ideas and approaches from a different field’, said Abecasis. But Abecasis also agreed that data sharing is not without challenges. ‘There are legitimate concerns about protecting the identity and privacy of research subjects and, once in a while, people do use data you share pre-publication to gain an advantage’, said Abecasis. ‘Still, there is no doubt we are moving in the right direction—expectations for data sharing and collaboration are so much more open than when I started’. Abecasis has felt fortunate to work with so many great collaborators. One of his most interesting collaborations has been his work with Dr David Schlessinger, Dr Francesco Cucca, Dr Serena Sanna and many others on the ‘SardiNIA project’. ‘When I first met David, and he described the idea of conducting a thorough genetic study in an isolated valley in Sardinia, I never thought it would happen’, remembered Abecasis. ‘It seemed so ambitious. But David and our Sardinian colleagues have boundless energy and real dedication, and the study probably accounts for most of my highly cited papers!’ ‘The work of Goncalo underscores the importance of the theoretical developments and their implementation in computational methods for the progress in current biomedical research, bringing genomic information closer to the study of the complex genetic basis of common diseases’, said Alfonso Valencia, chair of the ISCB's Awards committee. Abecasis feels truly honored and humbled to be the 2013 recipient of the Overton Prize. Abecasis also hopes that ‘If this award encourages members of the ISCB to bring some of their considerable expertise to bear on the big open problems in genetics, that would be an amazing outcome.’ During the past 20 years, the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference, and ISMB/ECCB 2013 will be the year's most important computational biology event globally. The ISMB conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB/ECCB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB/ECCB 2013 offers a strong scientific program and the broadest scope of any international bioinformatics/computational biology conference. ISMB/ECCB 2013 takes place July 19–23, 2013, at the Messe Berlin (ICC Berlin), Germany. For 2 days preceding the conference, additional opportunities including Satellite Meetings, Junior Principal Investigator Symposium, Student Council Symposium and a selection of Special Interest Group Meetings and Tutorials are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.

The International Society for Computational Biology (ISCB; http://www.iscb.org) honors a senior scientist each year for his or her outstanding achievements. The ISCB Accomplishment by a Senior Scientist recognizes a leading member of the computational biology community for his or her significant contributions to the field through research, service, and training. The 2013 ISCB Accomplishment by a Senior Scientist Award honors Dr. David Eisenberg of the University of California Los Angeles (UCLA). Dr. Eisenberg (Image 1) was selected the by ISCB's awards committee, which is chaired by Dr. Alfonso Valencia of the Spanish National Cancer Research Center (CNIO) in Madrid. Dr. Eisenberg will receive his awards and deliver a keynote address at the ISCB's 21st annual Intelligent Systems for Molecular Biology (ISMB) meeting. This meeting is being held jointly with the 12th European Conference on Computational Biology and will take place in Berlin, Germany on July 19–23, 2013 (http://www.iscb.org/ismbeccb2013). Image 1. David Eisenberg, UCLA. 2013 ISCB Accomplishment by a Senior Scientist Award: David Eisenberg David Eisenberg's love of medicine and science was cultivated first during his childhood by his father, a gentle and beloved pediatrician. Eisenberg recalled, “Every night after dinner he would make house calls. I saw how appreciated—even loved—he was in our village.” Eisenberg's father also stoked his scientific curiosity by encouraging him to try some experiments in their basement, including attempts to petrify an egg and to grow worms in chocolate. Eisenberg reminisced, “None of these [experiments] worked, but they were fun!” Eisenberg strongly considered following in his father's footsteps and pursuing a career in medicine. With that goal in mind, he focused his undergraduate studies on biochemical sciences at Harvard University. As a sophomore, he was assigned to Dr. John T. Edsall as a tutor. Edsall was a pioneering researcher in the field of biophysical chemistry, and under his guidance, Eisenberg had his first encounter with laboratory research. “In my junior year, he assigned me to read scientific papers, most of which baffled me, and at the end of that year, I started a research project in his lab, which became the subject of my senior thesis,” Eisenberg recounted. “After graduation, Dr. Edsall turned my thesis into a short paper which was published in Science.” In spite of Eisenberg's eye-opening undergraduate research experiences, he applied and was accepted to medical school. Edsall was also trained as a medical doctor, but Eisenberg remembered how “Dr. Edsall convinced me that if my goal was to improve the health of mankind, I might have a greater impact working in biochemistry, than as a practicing physician.” Eisenberg took Edsall's advice to heart and “finessed making an immediate choice by going to Oxford to study theoretical chemistry under Dr. Charles Coulson, one of the founders of quantum chemistry.” Edsall's guidance had also given him a strong foundation in math and physics, which served him well as a graduate student at Oxford as he recalled being “(just) able to work with Coulson on the energetics of hydrogen bonding.” Eisenberg's postdoctoral studies took him to Princeton in 1964 to work with Dr. Walter Kauzmann, well known for his discovery of the hydrophobic interaction. Eisenberg recollected his ambitious postdoctoral plan “to compute the energy of the hydrophobic interaction in myoglobin, the first protein with a known 3D structure. This plan now seems hopelessly naive: computers were not yet up to such a calculation, potential functions and theory had not advanced to the point that this was a practical problem, and the early protein crystallographers were not eager to release their atomic coordinates.” In light of these challenges, Eisenberg's work with Kauzmann culminated in “a monograph on ice and water, which, incidentally, is still in print 44 years later.” His failed postdoctoral research plan also opened his eyes. He knew that if he wanted to pursue protein energetics, which required knowing protein coordinates, he had to learn X-ray crystallography. Eisenberg's next postdoc took him “to Caltech to study X-ray crystallography with Richard Dickerson, who had been part of the team who had determined the structure of myoglobin.” His X-ray crystallography training was pivotal to establishing his own lab at UCLA, which focused on studying diverse protein structures. Melittin, a component of bee venom, was one of the first structures he determined with his then graduate student Tom Terwilliger. Eisenberg vividly recalled that, “At last I was able to get down to energetic calculations on a protein, and came up with the idea of the hydrophobic moment. This and related ideas gave me, for the first time, the feeling that I could make discoveries.” Eisenberg also remembers the excitement of solving the structure of diphtheria toxin dimer, which he worked on with John Collier, Senyon Choe, and Melanie Bennett (Brewer). He recalled the excitement that stemmed from Bennett's observation that “two monomers of the dimer swapped their third domains, and we called this phenomenon “3D domain swapping.” We explored the implications of 3D domain swapping, again calling on my background in energetics. Diphtheria toxin was the first structural example of 3D domain swapping; now there are hundreds.” Eisenberg's work on protein structures awakened his interest in how protein sequences related to 3D structures. While on sabbatical at the Laboratory of Molecular Biology in Cambridge, he worked with Andrew McLachlan and Mike Gribskov to develop methods to examine protein sequences and use profile analysis to predict the presence of potential structural motifs. These studies led to his work on 3D profiles with Jim Bowie and Roland Luethy, which Eisenberg has now seen “applied to many protein problems.” Burkhard Rost, president of the ISCB, considers Eisenberg's work on hydrophobicity profiling as groundbreaking because it “describes an important feature of the constituents of proteins (amino acids), namely their preferences to stay away from the solvent water (hydro = water, phobie = animosity). Many other outstanding, original methods followed for the prediction of protein structure and function; many of those methods were so visionary that they started entire fields of research.” The availability of the first complete genome sequences in the late 1990s inspired Eisenberg's work with “colleague Todd Yeates and our two talented postdoctoral fellows Edward Marcotte and Matteo Pellegrini, [in which] we found we could extract information on protein interactions from sequenced genomes.” These cutting edge studies resulted in several publications that showed how protein function and protein-protein interactions could be predicted from genome sequences. Eisenberg has focused his research over the last decade on studying amyloid-forming proteins. Several neurodegenerative diseases are associated with amyloid-forming proteins, including Alzheimer's, Parkinson's and amyotrophic lateral sclerosis (Lou Gehrig's) disease. “Just before the turn of the century, I realized that amyloid diseases represent the greatest unmet medical problem facing the world,” Eisenberg recounted. “And at the same time, I realized that structural and computational biology, which have illuminated other areas of biomedicine so well, have not been widely applied to the fundamental problems of amyloid disease. In particular, there had been almost no single crystal X-ray studies of amyloid-forming proteins.” The use of computational biology with this structural data has helped support the definition of the “amyloid state” of proteins. “Bioinformatics and computational biology are great partners with structural biology. Using the tools together can be surprisingly powerful,” said Eisenberg. Eisenberg's group has studied the structural basis of how normal proteins convert to amyloid fibrils. They have gained great insight into this conversion process by determining the atomic structures of the spines of many different types of amyloid fibrils. Eisenberg also acknowledges that, “Having several friends afflicted with amyloid disorders is a great inspiration. I would love to be able to help them, and others. If we can, it would validate Dr. Edsall's advice that sometimes biochemists can do as much, or more, to help mankind than physicians.” Eisenberg remains humble about his accomplishments. When asked about being the recipient of the ISCB Senior Scientist Accomplishment Award, he felt “honored, but perhaps over-honored. There are many others who are equally, or more, deserving of this recognition.” But he also recognizes that this award helps highlight the importance of studying amyloid diseases, especially by using the tools of computational biology. Eisenberg speaks warmly of the mentors that have guided and shaped his scientific training. “I was enormously fortunate to find myself in the research groups of four great mentors: John Edsall, Charles Coulson, Walter Kauzmann, and Richard Dickerson, not to mention my father. All were creative scientists, and also humanists. Watching them I saw their pleasure in scientific discovery, and also saw their insistence on fairness to all those involved in the process of science.” Their examples have not only served him well as a scientist, but also as a mentor. Eisenberg delights in working with trainees because he loves “their eagerness to learn and to succeed, and their willingness to think freshly about hard problems.” Eisenberg's scientific curiosity remains insatiable, and when asked for advice to motivate young scientists, his sage answer was “work on fundamental problems, maintain your curiosity, and above all, persevere.”

Computational biology and bioinformatics have grown into cutting-edge interdisciplinary fields essential to every realm of basic research in this age of modern genomics and open-source software. In light of this, the International Society for Computational Biology (ISCB) saw a need to estabish a program for the organization that recognized its members who made significant contributions to the fields, as well as service to the Society. A task force led by Mona Singh was formed to develop a program to recognize and honor this unique group of researchers. In early 2009, ISCB established its Fellows Program. The first group elected into this distinguished group were past recipients of the ISCB Accomplishment by a Senior Scientist Award, which was established in 2003. Since then, Fellows have been identified through a rigorous process involving a call for nominations from the ISCB membership and selection by the Fellows Selection Committee, which in past years has included the ISCB Board of Directors and previously selected Fellows. The distinction of an ISCB Fellow is based on: Nomination by an ISCB member submitting a short endorsement for the nominee, a detailed half-page statement of motivation justifying the nominee, and a CV of the nominee. Nominees must have demonstrated excellence in research, service to the ISCB community, education, and/or administration. Nominees must have been a member of the Society for at least three of the last six years. Selection of new Fellows each year is limited to half of one percent of the previous year's membership and includes the Senior Scientist Award winner. The 2013 ISCB Fellows epitomize the mission of ISCB to advance scientific understanding of living systems through computation and clearly fulfill the goals of the Fellows Program. Each Fellow has made outstanding contributions to computational biology through research, teaching, and service to the scientific community. On behalf of the ISCB Board of Directors and Fellows Committee, congratulations!