During the course of our personal and professional lives, we spend a significant amount of time communicating with others.In fact, communication is one of the most important, but possibly also one of the hardest, things we do, having the power to bring individuals and communities together or create divisions.Getting it right is therefore crucial.Modern technologies have had a significant impact on the ways in which we are now able to communicate, allowing us to share our thoughts with colleagues, family, or friends at the click of a button.But communicating more quickly does not always result in better communication-the technologies we use often divorce us from the visual clues that are so crucial to understanding each other's true meaning and make it easy to misinterpret each other's real intentions.For this reason, our interactions can sometimes be unexpectedly difficult or can go unaccountably wrong.Given that communication is vital to the health and productivity of relationships, how can we best make our interactions work, and how can we resolve situations when they arise?The following are 10 simple rules based on our experience that we hope will help.Many of these rules can apply to the kinds of communication we may have with colleagues, family, or friends.However, we focus this article on the professional environment: we begin with suggestions to help avoid disagreements or to help stop them turning into serious conflicts; we then reflect on steps that might help to resolve situations that have become confrontational.Most interactions with colleagues are cordial and are working towards a common goal.Sometimes, however, because of differing views, misinterpretation of something said, or just because you're having a bad day, communications can go awry and become heated; from this point, without resolution, awkward situations can quickly escalate.Practicing effective communication skills before a confrontation arises, or during a confrontation, is the topic of this article.For more general ideas about engaging in successful collaborations, see [1].To delve further into the area of conflict management in the work environment, see [2,3].To keep this contribution manageable, we have confined ourselves to peer-to-peer communication and not considered a larger ecosystem of interactions in which conflict occurs.We feel that is a separate contribution that should be written. Rule 1: Always treat people with equality and respectWhether interacting with your peers or not, treat people courteously.Don't prejudge individuals based on their rank or perceived academic abilities, or worse, their gender, race, or sexual orientation.Be polite, and treat everyone equally and fairly.

What began as a one-off in 2005 as Ten Simple Rules for Getting Published [1] has, in thirteen years, now multiplied a hundredfold to become One Thousand Simple Rules for many aspects of one's professional development and led to Quick Tips in the journal's Education section.This milestone of a thousand rules has been reached thanks to the unselfish work of all stakeholders-authors, editors, reviewers, and readers.Let's face it, writing, editing or reviewing a Ten Simple Rules (TSR) article is not the same as a publication that advances a scientific field.What it is going to get you is the satisfaction of knowing you have passed on a part of your experience in a form that is easily understood and acted upon by those following in your footsteps and hence have a very different kind of positive impact on science.Thank you.On the other hand, as a reader the TSRs might contribute in some small way to you getting tenure, or whatever else you care about in your professional life."How to write a review, by M Pautasso.It changed my approach to writing reviews."Anonymous, Academic faculty "Ten Simple Rules for Reproducible Computational Research, and other articles related to computational biology, programming, etc.They really helped in organizing my projects and code more efficiently."

SUMMARY: Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events; for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills; for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide. AVAILABILITY AND IMPLEMENTATION: http://mygoblet.org/training-portal.

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.

A Quick Guide to Genomics and Bioinformatics Training for Clinical and Public Audiences

Rapid advances in the life sciences and in related information technologies necessitate the ongoing refinement of bioinformatics educational programs in order to maintain their relevance. As the discipline of bioinformatics and computational biology expands and matures, it is important to characterize the elements that contribute to the success of professionals in this field. These individuals work in a wide variety of settings, including bioinformatics core facilities, biological and medical research laboratories, software development organizations, pharmaceutical and instrument development companies, and institutions that provide education, service, and training. In response to this need, the Curriculum Task Force of the International Society for Computational Biology (ISCB) Education Committee seeks to define curricular guidelines for those who train and educate bioinformaticians. The previous report of the task force summarized a survey that was conducted to gather input regarding the skill set needed by bioinformaticians [1]. The current article details a subsequent effort, wherein the task force broadened its perspectives by examining bioinformatics career opportunities, surveying directors of bioinformatics core facilities, and reviewing bioinformatics education programs.

Educating biologists and computational biologists in methods and analyses is an ever-growing challenge.The amount of data and tools available to the scientific community continue to grow, and with that, there is a growing need to teach how to get the most out of this information.The PLOS Computational Biology Education section was launched in January 2006 [1] to address this challenge, with the first contribution published in April of that year [2].In these past eight years, we have published more than 50 Education articles on different topics and have started two specialized Education collections: ''Bioinformatics: Starting Early'' [3], which addresses the needs of teaching bioinformatics at the secondary school level, and the first PLOS online textbook, ''Translational Bioinformatics'' [4].After eight years in the role of editor of this section, I have decided that it is time to step aside to allow fresh ideas to be introduced into building the Education section and new directions to be followed as our science continues to mature.I am delighted that

The International Society for Computational Biology (ISCB) Education Committee (EduComm) promotes worldwide education and training in computational biology and bioinformatics and serves as a resource and advisor to organizations interested in developing educational programs. The topic of curricula for bioinformatics programs has long been of interest to ISCB and EduComm. Dr. Russ Altman, a founding board member and past president of ISCB, has been associated with one of the first bioinformatics degree programs (at Stanford University) and wrote an article on this topic [1]. Dr. Shoba Ranganathan, as chair of EduComm a decade ago, began organizing a yearly Workshop on Education in Bioinformatics (WEB) at Intelligent Systems for Molecular Biology (ISMB) meetings that generated exchange of information and many productive discussions. Curriculum development was one aspect of bioinformatics education covered in these sessions [2].

Fran Lewitter is Education Editor of PLoS Computational Biology. Given the availability of free, online genomic databases and tools for the analysis of biological data, it is now feasible to teach bioinformatics in the high school classroom [1]. There are a number of reasons why it is appropriate and desirable to introduce bioinformatics at the high school level. Students can engage in inquiry-based activities that involve approaching real-world problems using 21st century skills, while being tailored to high school biology frameworks. Many tools, such as 3-D protein visualization software, allow for differentiated and highly interactive instruction. The foremost reason may be that students can develop a research toolkit that they will be able to use subsequently during college and beyond. As a high school science teacher for the past 23 years, I (DF) have had the opportunity to incorporate bioinformatics into my courses to enrich the teaching of concepts of molecular biology, human biology, genetics, and evolution, providing increased opportunities for effective differentiated instruction and individual student research. This past experience has inspired the creation of this set of Ten Simple Rules. It is important to distinguish between curricula designed to teach the fundamentals of bioinformatics and those that utilize bioinformatics as a teaching tool. Examples of both types of successful teaching can be found in Text S1, Text S2, and Text S3.

Bioinformatics is now an integral part of biology and biological research. The field began with a few people from other disciplines teaching themselves and each other the techniques that are now considered commonplace. These pioneers then began graduate programs [1]–[3] to educate the next generation. Those early graduate students typically came as bench biologists or as computer scientists, both groups requiring significant time to “hybridize”. Not surprisingly, this then led to undergraduate majors in bioinformatics to better prepare students for graduate school and research careers in bioinformatics. In addition, teaching bioinformatics in undergraduate biology classes is also a priority [4], [5]. Through the Education section of PLoS Computational Biology we have tried to support this evolution through a collection of educational articles pertinent to the undergraduate level and beyond. It is only natural that we would take the next step [6]. We now introduce a subsection of the Education section with articles devoted to teaching bioinformatics in secondary schools that is derived from the work of the Education committee of the International Society for Computational Biology (ISCB), who identified a need to address the issue of incorporating bioinformatics into secondary school biology classes. They also recognized the interest among researchers to build and participate in outreach programs at the secondary school level given that many funding agencies worldwide encourage such a component in grant applications. To move the ball forward on secondary school bioinformatics education, at ISCB's 2010 international conference, Intelligent Systems in Molecular Biology (ISMB), the ISCB Education committee organized a half-day tutorial aimed at secondary school biology and chemistry teachers in the Boston area interested in learning about bioinformatics and how to include it in their curricula. The tutorial also attracted researchers involved in organizing or formulating outreach programs in their community. The main focus of the ISMB tutorial was the presentation of lesson plans by a secondary school teacher (David Form, a biology teacher at Nashoba Regional High School, Bolton, Massachusetts) who has successfully incorporated bioinformatics into his courses for more than five years. His is one example of such an effort and is embraced in the Ten Simple Rules and its supplementary material found in this issue. Also in this issue we have an article by Suzanne Gallagher and colleagues on the experience of teaching secondary school level bioinformatics in Boulder, Colorado. There are many examples of outreach efforts to high school students that we would like to feature in coming months, which incorporate bioinformatics into their programs (see Table 1). Table 1 Examples of Online Resources and Outreach Programs. There are many other examples of educators doing similar work in school districts worldwide. A recent issue of Briefings in Bioinformatics was dedicated to bioinformatics education [7] with a specific example of programs for secondary school students [8], [9].The ISCB Education committee is building a resource of information useful to secondary school teachers who would like to incorporate bioinformatics into their curriculum. In addition, the committee has begun to explore how to include bioinformatics in Advanced Placement courses and exams in the United States, which we also hope to feature in the Education section of the journal. We encourage feedback of any form, including comments on this editorial, and hearing about your experience teaching bioinformatics to secondary school students.

There are many issues to consider when establishing and building a Bioinformatics Core Facility. Mission, funding, scope of projects, organizational context, infrastructure, software support, and training are among the many to consider. One of the most important and arguably the most critical to success is building the team to execute the mission of the group. We devote this Perspective to our thoughts on this and related issues and how they affect the mid- to long-term success of the Core Facility, in particular its ability to make strong scientific contributions. Although Bioinformatics Core Facilities come in many different variants, depending on their history, mission, and institutional environment, they all share one challenge during the initial and consolidation phase: to recruit and retain the right people who thrive in such roles. One of the key requirements is that team members are able to learn new methodologies and expand into new areas as needed by the evolution of research methods. Bioinformaticians with sufficient and diverse experience are a relatively rare species. Therefore, hiring in the initial phase of a Core Facility's development often has to focus on bioinformaticians with experience in at least some of the key areas the group is expected to work in. A more mature and sustainable setup is often characterized by at least two to three senior staff with diverse experience but different focus areas, plus more junior ones in different stages (students, postdocs, and new staff). Such units are then able to offer the expertise required to competitively address difficult problems at the forefront of science. In environments that expect considerable scientific contributions from the Bioinformatics Core Facility, one of the major success factors is to have people on the team who have extensive formal background in biology plus several years of experience in applying bioinformatics methods to biological problems. Many projects will require considerable biological insight in addition to hands-on experience with bioinformatics tools and scripting (in languages such as Perl, R, etc.), and at least basic knowledge of statistics and experimental design. In addition to those “in silico biologists”, some projects will require people with more extensive background in areas that biologists often cannot cover well, such as data mining and analysis, computer science, structural biology and biochemistry, more advanced statistics and experimental design, software engineering, theoretical biology, and so on, depending on the institution and the mission of the Facility. In such mature Facilities, staying up to date with the most relevant new approaches becomes attainable, as different experts can efficiently share ideas taken from the literature and from scientific meetings. Achieving a high level of quality in providing scientific and technical solutions depends on several factors that include: a) allowing the bioinformaticians to spend 20%–40% of their time to develop mid-term focus areas that combine certain types of biological questions with related bioinformatics approaches; b) encouraging regular discussion on best practice within the unit, in particular the pros and cons of different approaches, and related resources; c) careful selection of the most relevant datasets and methods for a given problem (which can take some time if there isn't sufficient overlap with previous projects); d) designing solutions that, if possible, combine independent lines of evidence to make results as reliable and informative as possible; e) meaningful communication with the experimentalists on the scientific goals and their context (in many cases the formulation of the original request is the starting point of a discussion that results in solutions that address the main underlying problems more effectively), and what can be expected from the Facility (to avoid disappointments due to unrealistic expectations, which can be a major problem); and f) communicating the results to the experimentalist in a way that works for the target audience (often requiring many iterations of analyses and lab work). As a measure of the maturity of the Bioinformatics Core Facility, not only will the contributions be valued by at least the early adopters in the institution, but the latter may then start to request input from bioinformatics experts in data-intensive projects that are designed as true interdisciplinary team efforts from the outset. For many bioinformaticians, this is where they always wanted to be. An early involvement of experienced bioinformaticians will usually have positive effects on the quality and relevance of the experimental design, and on the relevance of the produced data for the bioinformatics approaches that are needed to answer the scientific questions at hand. Many Bioinformatics Core Facilities, however, do not reach that mature stage, and are caught, in extreme cases, in a “firefighting mode”, a vicious cycle between highly diverse, mostly urgent and hardly prioritized requests, and insufficient resources for developing high-quality solutions that make significant contributions to the output of the institution. Not surprisingly, it is notoriously difficult to attract and retain good people in such environments. Unfortunately, the problem is sometimes not analyzed systematically and recognized as such by the stakeholders. In such situations, open communication about the challenges and formalization of the communication to the main stakeholders in the form of a Core Facility committee can be a solution, if some understanding of the resources required to adequately address problems has developed. The first two to three years are crucial, therefore, in many cases for building up the unit, in partnership with at least a few scientists who have sufficient interest and vision, and a strategic interest in taking advantage of bioinformatics capabilities in their research. Once the success stories are ready for presentation and for other forms of communication, this can help to extend institutional support for developing the Core Facility into the mature stage described above, which provides additional resources for supporting a larger group of customers. In our experience, which includes discussions with other managers of Bioinformatics Core Facilities within the “bioinfo-core” community (http://www.bioinfo-core.org), the following factors can be crucial for overcoming the often-difficult first years. Developing the mission objectives of the Core Facility: does it include or exclude scientific collaborations (and co-authorship as an evaluation criterion), application development and hosting, statistics and experimental design support, educational campaigns, taking care of hardware, development of innovative bioinformatics methods, and so on? Is there an understanding of the resources needed to address those problems adequately? Deciding on the right mix of people to be hired for this environment, after getting to know the early adopters and the institution to a degree that allows the selection of the most relevant skill sets. Developing a good balance between small projects with a quick turnaround and larger collaborations that require in-depth literature study, exploration of alternative approaches, and extensive discussion (the latter are crucial for developing good showcases and strategic partnerships, and usually result in co-authorship on publications; small and swift projects, on the other hand, can help to build up partnerships and mutual understanding). Finding strategies for addressing problems quickly and effectively (and related best practice, see above). This often includes reusable tools and datasets and the development of a dedicated bioinformatics computing environment that allows quick prototyping of alternative solutions to problems. Transparent prioritization and careful time management helps in dealing with demand overload. This usually requires regular communication with partners and stakeholders, and helps to avoid situations in which staff become too scattered in terms of the different types of ongoing projects at a particular time. Proper management of the above challenges will have considerable impact on the quality of the solutions and often also affects the retention of experienced staff. The head of the Bioinformatics Core Facility needs to make sure that those who request help from bioinformatics experts are comfortable with the process and the people (a certain degree of informality and getting-to-know-each-other can be very helpful here), while also balancing this goal of responsiveness and customer focus with the ability to manage expectations and urgent requests during times of high demand to provide an environment that allows sufficient time for quality work and capability development. This sometimes also includes the management of situations in which the bioinformaticians are going off track. Staying connected: keeping in touch with new trends in the research strategy of individual investigators, understanding what is most relevant, and regularly collecting feedback on the relevance of the Core Facility.

Biomedical research is benefiting from the wealth of new data generated in the laboratory through new instrumentation, greater computational resources, and massive repositories of public domain data. Using these data to make scientific discoveries is sometimes straightforward, but can be complicated by the number and breadth of public sources available to the researcher as well as by the plethora of tools from which to choose. Complex searches, analyses, or even storage needs require more computational expertise than that available within an individual laboratory. As biomedical researchers develop more computational skills, this may change over time. Having a centralized group of experts in computational biology can be of great value to the experimental biologist, and, recognizing this, many organizations have invested in building a team of computational biologists, bioinformaticists, and research IT services to address the needs of the investigators. This Editorial presents our views on the benefits and challenges of centralizing these activities. In order to benefit from expertise among existing teams of experts around the world, the “Bioinfo-Core” group was formed during the ISMB 2002 meeting in Edmonton, Canada, with approximately 25 initial members. Since then, the group has expanded in both organization and interest. Our worldwide membership now includes more than 150 people who administer centralized bioinformatics and research computing facilities within diverse organizations, including academia, independent research institutes, academic medical centers, and industry. Additionally, the group holds quarterly meetings via teleconference, continues an annual face-to-face meeting at ISMB (averaging 40–60 people), and hosts a mailing list and Wiki (http://www.bioinfo-core.org) to further communication.

he need to train biologists in computational methods is greater than ever before.Recently, I asked an MIT Biology Professor if his newer graduate students were more knowledgeable in bioinformatics and computational biology than in past years.He hesitated and said he needed to think more about it; there wasn't a clear answer.What is clear, however, is that most graduate students are computer savvy and are comfortable using computers for writing and searching the Web.They may also have used computational tools on the Web but with little understanding of the guts of the algorithm.It is this group of students, as well as those further along in their careers, whom we hope to reach with the publication of learned articles in the Education section of PLoS Computational Biology.Regardless of readers' levels of experience, we strive to provide a starting point for inquisitive minds.The Education column of PLoS Computational Biology was introduced one year ago [1] with the goal to provide both practical and background information on important computational methods used to investigate interesting biological problems.During this first year, we have made strides toward this goal by publishing three excellent Education articles on diverse topics.Our first tutorial was presented in April 2006 and was well-received, staying on the list of PLoS Computational Biology Top 10 articles downloaded well after its publication date.Practical Strategies for Discovering Regulatory DNA Sequence Motifs by MacIsaac and Fraenkel [2] explores microarray experiments, a common way of investigating gene expression.Identifying sequence motifs in sets of differentially regulated genes can provide insights into the mechanisms of regulation, but care must be taken to avoid the many spurious motifs that occur in genomic sequences.This first tutorial provides strategies to improve the chances of finding functional regulatory sites.The continued interest in this first of many tutorials to come demonstrates the need for high-quality tutorials for colleagues at all career levels.