MOTIVATION: Wikipedia is a vital open educational resource in computational biology; however, a significant knowledge gap exists between English and non-English Wikipedias. Reducing this knowledge gap via intensive editing events, or "editathons," would be beneficial in reducing language barriers that disadvantage learners whose native language is not English. Results: We present a framework to guide educators in organizing editathons for learners to improve and create relevant Wikipedia articles. As a case study, we present the results of an editathon held at the 2024 ISCB Latin America conference, in which ten new articles were created for the Spanish-language edition of Wikipedia. We also present a web tool, "compbio-on-wiki," which identifies relevant English Wikipedia articles missing in other languages. We demonstrate the value of editathons to expand the accessibility and visibility of computational biology content in multiple languages. AVAILABILITY AND IMPLEMENTATION: Source code for the compbio-on-wiki Toolforge site is available at: https://github.com/lubianat/compbio-on-wiki.

The COVID-19 pandemic led to devastating physical, psychological, and financial impacts on millions of people across the world. Amidst a rapidly evolving research landscape, the global scientific community was forced to swiftly adapt to novel working methods, including remote collaboration tools, virtual conferences, and online research platforms. Surveys of life sciences researchers have indicated that computational biologists experienced less disruption and a smoother transition to remote working than experimental biologists, due to their reduced reliance on laboratory equipment. Despite this adaptability, the sudden shift to remote work, compounded by stress and social isolation, has posed significant mental health challenges for these workers. However, remote work has also facilitated opportunities for more flexible work arrangements and increased collaboration across geographical boundaries. To investigate these impacts, we conducted surveys of computational biologists during the Intelligent Systems for Molecular Biology (ISMB) conferences in 2020 and 2021, which were held virtually due to the COVID-19 lockdowns. This study implements a thorough statistical analysis of the survey results to offer insights into the repercussions of the lockdowns on researchers and their work. Key areas of investigation include the effects of institutional support (or lack thereof), the difference in productivity compared to pre-lockdown levels, and the significance of gender in determining these impacts. Notably, a lack of institutional support with regard to mental health and finances was shown to have a significant negative effect on early-career researchers. Although limited by a small sample size, our study sets the stage for a more robust exploration of these trends in future research. Importantly, by illuminating the challenges and opportunities arising from the COVID-19 pandemic and lockdowns, our study offers hope for potential solutions supporting the well-being of early-career researchers in unprecedented circumstances.

MOTIVATION: Wikipedia is a vital open educational resource in computational biology. The quality of computational biology coverage in English-language Wikipedia has improved steadily in recent years. However, there is an increasingly large 'knowledge gap' between computational biology resources in English-language Wikipedia, and Wikipedias in non-English languages. Reducing this knowledge gap by providing educational resources in non-English languages would reduce language barriers which disadvantage non-native English speaking learners across multiple dimensions in computational biology. RESULTS: Here, we provide a comprehensive assessment of computational biology coverage in Spanish-language Wikipedia, the second most accessed Wikipedia worldwide. Using Spanish-language Wikipedia as a case study, we generate quantitative and qualitative data before and after a targeted educational event, specifically, a Spanish-focused student editing competition. Our data demonstrates how such events and activities can narrow the knowledge gap between English and non-English educational resources, by improving existing articles and creating new articles. Finally, based on our analysis, we suggest ways to prioritize future initiatives to improve open educational resources in other languages. AVAILABILITY AND IMPLEMENTATION: Scripts for data analysis are available at: https://github.com/ISCBWikiTeam/spanish.

MOTIVATION: Wikipedia is one of the most important channels for the public communication of science and is frequently accessed as an educational resource in computational biology. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further improvement in quality, especially when compared to related scientific fields such as genetics and medicine. Facilitating involvement of members from ISCB Communities of Special Interest (COSIs) would improve a vital open education resource in computational biology, additionally allowing COSIs to provide a quality educational resource highly specific to their subfield. RESULTS: We generate a list of around 1500 English Wikipedia articles relating to computational biology and describe the development of a binary COSI-Article matrix, linking COSIs to relevant articles and thereby defining domain-specific open educational resources. Our analysis of the COSI-Article matrix data provides a quantitative assessment of computational biology representation on Wikipedia against other fields and at a COSI-specific level. Furthermore, we conducted similarity analysis and subsequent clustering of COSI-Article data to provide insight into potential relationships between COSIs. Finally, based on our analysis, we suggest courses of action to improve the quality of computational biology representation on Wikipedia.

The International Society for Computational Biology (ISCB) is pleased to announce the 5th ISCB Wikipedia Competition. The competition has been run annually since 2012 and awards students and trainees for the best contributions to computational biology-related articles (Bateman et al., 2013). ISCB runs the competition in collaboration with WikiProject Computational Biology, a group of around 130 editors overseeing the roughly 1300 computational biology-related articles on Wikipedia. Entry to the competition is open internationally, to students and trainees of any level, both as individuals and as groups. Further information about the competition can be found here: https://en.wikipedia.org/wiki/WP:ISCB2016. The 2016 competition began on 13 July 2016, coinciding with the Intelligent Systems for Molecular Biology (ISMB) conference, and will end on 31 December 2016. Each article entered in the competition will be reviewed by students nominated by the ISCB Student Council, and a shortlist of entries will be examined by a judging panel. The winners will be presented with their awards at ISMB/ECCB 2017 in Prague. As of the 2015 competition, entries in languages other than English are welcomed; the 2015 competition saw the creation and expansion of several articles in Spanish, and the newly-created Spanish Wikipedia entry for BioJava was awarded second prize. The 2015 competition was also the first to include a Wikidata component. Similar to Wikipedia, Wikidata is a collaboratively edited knowledge base, intended to provide a common source of data to be used primarily by Wikipedia but also the general public. Launched in 2012, Wikidata plays an increasingly important role in communicating all types of science to the public, and the inclusion of a Wikidata component in the competition aims to improve data content related to computational biology. In the 2015 competition, prizes were awarded for contributions to the Vienna RNA Package and Docking Wikidata items. We hope to see an increased number of contributions in other languages and to Wikidata content in this year's competition. As the 2016 competition begins, the ISCB and WikiProject Computational Biology remain keen to grow the quality and depth of computational biology coverage over all Wikimedia projects and wish to encourage the widest possible range of students and trainees to participate. We particularly encourage teachers, tutors and lecturers to use the competition in their courses, with contributions to relevant Wikipedia or Wikidata content as part of a class assignment. Wikipedia provides information and resources for running editing projects as part of school and university classes (see https://en.wikipedia.org/wiki/WP:SUP), and PLOS Computational Biology has also published tips for Wikipedia beginners (Logan et al., 2010). As described previously, unlike traditional class assignments, contributing to Wikipedia means that students' work will become publicly available to future researchers. Several courses already contain such a component; a 2015 course on Biological Clocks at Washington University in St. Louis, Missouri added a significant amount of information on the topic of chronobiology, including new biography articles on notable researchers in the field. Besides the primary contribution to public knowledge, the competition also provides the opportunity to develop effective communication skills with a range of audiences, and the ability to function effectively as part of a team for group entries, two of ISCB's core bioinformatics competencies (Welch et al., 2014). We hope that the ISCB Wikipedia Competition will continue to grow and make an increasing contribution to both the quality of computational biology information freely available online and the training of the next generation of computational biologists.

Open access to scientific information is a core principle of the International Society for Computational Biology (ISCB). This principle is shared by the Wikimedia Foundation, with its primary goal to collect, develop and disseminate free and open-access educational content. Consequently, ISCB has and continues to foster strong links with several Wikimedia projects, particularly Wikipedia. To this end, ISCB works closely with WikiProject Computational Biology (WCB), a group of around 130 editors overseeing Wikipedia articles relating to computational biology and bioinformatics. In 2017, WCB celebrates its 10th anniversary, having grown to cover more than 1,300 articles in the English Wikipedia. This article serves to acknowledge past ISCB–WCB collaborations, release the results of the 2016–2017 ISCB Wikipedia competition, officially announce the 2017–2018 competition, and explore exciting future directions, including the potential role of WCB in classroom education for computational biology. WCB’s 10-year history has been marked by a number of collaborative efforts with ISCB. These include PLOS Topic Pages, ISCB’s annual Wikipedia competition, and events at ISCB conferences. Topic Pages are an initiative pioneered in 2012 by PLOS Computational Biology, one of the official journals of ISCB, to create high-quality Wikipedia articles while also providing trainees with an opportunity to build a publication record. A topic page is a review article written for the general public and according to Wikipedia guidelines that is simultaneously published by PLOS and as a Wikipedia article. Since its inception, 10 high quality, in-depth articles on topics in computational biology have been created. Also since 2012, ISCB and WCB have held an annual Wikipedia competition, offering cash prizes and memberships to students and trainees for the best contributions to computational biology-related Wikipedia articles and Wikidata entries (Bateman et al., 2013; Kilpatrick, 2016). This competition has been highly successful in driving the improvement of coverage of computational biology within Wikipedia, having drawn a total of 144 entries over just five years. Beyond the ISCB Wikipedia Competition and PLOS Topic Pages, the partnership between the ISCB and WCB has continued to grow. Following tutorials at ECCB 2012 and ISMB 2014 which provided a practical introduction to editing Wikipedia for scientists, the ISCB held a Wikipedia and Wikidata editathon at ISMB 2016 as part of the celebrations for the Wikipedia Year of Science. Another editathon will be held at ISMB/ECCB 2017 on an all-day drop-in model, and we invite attendees regardless of their previous experience with Wikipedia editing. We envisage similar joint events in the future which will help to improve the coverage of computational biology and bioinformatics on Wikimedia projects. There were 17 substantial entries into the 2016–2017 Wikipedia competition, including five entries for non-English articles. A panel of six ISCB judges considered these articles, as in previous competitions, based on the clarity of the writing, depth of knowledge of the subject, and quality of figures and images used. The judging panel selected the following as the winners of the 2016–2017 ISCB Wikipedia competition: First prize: Yadi Zhou (Ohio University, USA) for improvements to the Smith-Waterman algorithm article, in both English and Chinese Wikipedia. Second prize: Charlotte Klimovich (Ohio University, USA) for improvements to the Margaret Oakley Dayhoff article. Third prize: Nicole Wheeler (University of Canterbury, New Zealand) for improvements to the Pfam article. During the 2017–2018 academic year, ISCB is running the 6th annual ISCB Wikipedia Competition in collaboration with WCB. Entry to the competition is open internationally to students and trainees of any level, both as individuals and as groups. As in previous years, the ISCB encourages competition entries for contributions to Wikipedia in any language, and contributions to Wikidata items. Further information about the competition can be found here: https://en.wikipedia.org/wiki/WP:ISCB2017 The competition will begin on 21 July 2017, coinciding with the ISMB/ECCB 2017 conference, and will end on 31 December 2017. Each article entered in the competition will be reviewed by students nominated by the ISCB Student Council, and a shortlist of entries will be examined by a judging panel. The winners will be presented with their awards at ISMB 2018 in Chicago. The ISCB also sees a role for WCB in collaborating with the ISCB Education Committee which, as part of its remit, seeks to define curriculum guidelines for bioinformatics courses (Welch et al., 2016). One potential area of work may be to use the current draft guidelines in order to identify a subset of Wikipedia articles which would provide a ‘core’ set of articles for a bioinformatics curriculum. Clearly these articles should be as complete as possible and should be prioritized for improvement by WCB members. The ISCB suggests that Wikipedia also has scope for helping to refine the curriculum guidelines. As an example, Wikipedia keeps viewing statistics for each of its articles; these show that the Bioinformatics article page was viewed over 41 000 times in January 2017 alone and the most-viewed WCB article (on CRISPR) was viewed almost 140 000 times in the same period. These viewing statistics may play a useful role in identifying areas of the curriculum that are of particular importance and therefore should be emphasized in future versions of the curriculum. We also encourage teachers, tutors and lecturers at all levels to use the ISCB Wikipedia competition as part of their class assignments. For example, by having students ‘claim’ a Wikipedia article for the competition, with their contributions over a short, defined period in the fall semester marked by the instructor. Wikipedia provides information and resources for running editing projects as part of classroom activities and the “Ten Simple Rules for Editing Wikipedia” (Logan et al., 2010) also provides an excellent resource for those new to Wikipedia editing. Besides the competition, there are a number of ways in which Wikipedia may be used in a classroom setting. For example, both undergraduates and graduate students may ‘claim’ an article to improve as a short class project to be evaluated by the tutor. Incentives such as the prospect of appearing on the front page of Wikipedia as a ‘Did you know?’ article can help to provide extra motivation. For graduate students, a Wikipedia article can potentially be expanded into a PLOS Topic Page (Wodak et al., 2012), which offers an opportunity to build a publication record, and can grant a head start on writing a thesis introduction. As noted previously, the collaborative writing environment of Wikipedia in particular encourages critical thinking and improves research skills. ISCB and WCB have spent the last decade working together to improve access to information about computational biology by fostering the creation of high-quality Wikipedia articles. The results of this have been encouraging. A paper in 2013 (Bateman et al., 2013) reported on the state of articles within the scope of WCB. Since then, almost 200 new articles have been added and many of the shortest articles (known as stubs) have been expanded (Fig. 1). However, a significant number of articles still remain at ‘Start class’ or lower, indicating weaknesses in many areas. ISCB and WCB are keen to expand on the depth and quality of articles relating to computational biology and encourage students and trainees at all levels to take part in the ISCB Wikipedia Competition, write topic pages, and drop in to the Wikipedia Editathon at ISMB/ECCB 2017. We look forward to continued collaborations and efforts by the entire community towards enhancing and disseminating humanity’s knowledge of computational biology. Wikipedia computational biology articles rated for both quality and importance by WCB. Quality levels are ordered from highest to lowest, beginning with ‘Featured Articles’ (considered to be amongst the best articles in Wikipedia) and ‘Good Articles’ (articles which meet a core set of Wikipedia editorial standards but are not FA quality). List articles are not rated for quality (Color version of this figure is available at Bioinformatics online.) Conflict of interest: none declared.

The International Society for Computational Biology (ISCB) is pleased to announce the 5th ISCB Wikipedia Competition.The competition has been run annually since 2012 and awards students and trainees for the best contributions to computational biology-related articles [1].ISCB runs the competition in collaboration with WikiProject Computational Biology, a group of around 130 editors overseeing the roughly 1,300 computational biology-related articles on Wikipedia.Entry to the competition is open internationally to students and trainees of any level, both as individuals and as groups.Further information about the competition can be found here: https://en.wikipedia.org/wiki/WP:ISCB2016.The 2016 competition began on 13 July 2016, coinciding with the Intelligent Systems for Molecular Biology (ISMB) conference, and will end on 31 December 2016.Each article entered in the competition will be reviewed by students nominated by the ISCB Student Council, and a shortlist of entries will be examined by a judging panel.The winners will be presented with their awards at ISMB/ECCB 2017 in Prague.As of the 2015 competition, entries in languages other than English are welcomed; the 2015 competition saw the creation and expansion of several articles in Spanish, and the newly-created Spanish Wikipedia entry for BioJava was awarded second prize.The 2015 competition was also the first to include a Wikidata component.Similar to Wikipedia, Wikidata is a collaboratively edited knowledge base, intended to provide a common source of data to be used primarily by Wikipedia but also the general public.Launched in 2012, Wikidata plays an increasingly important role in communicating all types of science to the public, and the inclusion of a Wikidata component in the competition aims to improve data content related to computational biology.In the 2015 competition, prizes were awarded for contributions to the Vienna RNA Package and Docking Wikidata items.We hope to see an increased number of contributions in other languages and to Wikidata content in this year's competition.As the 2016 competition begins, the ISCB and WikiProject Computational Biology remain keen to grow the quality and depth of computational biology coverage over all Wikimedia projects and wish to encourage the widest possible range of students and trainees to participate.We particularly encourage teachers, tutors, and lecturers to use the competition in their courses, with contributions to relevant Wikipedia or Wikidata content as part of a class assignment.Wikipedia provides information and resources for running editing projects as part of school and university classes (see https://en.wikipedia.org/wiki/WP:SUP), and PLOS Computational Biology has also published tips for Wikipedia beginners [2].As described previously, unlike traditional class assignments, contributing to Wikipedia means that students' work will become publicly available to future researchers.Several courses already contain such a component; a 2015 course on Biological Clocks at Washington University in St. Louis, Missouri added a significant amount of information on the topic of chronobiology, including new biography articles on notable researchers in the field.Besides the

The Curriculum Task Force (CTF) of ISCB’s Education Committee seeks to define curricular guidelines for those who educate or train bioinformatics professionals at all career stages. A recent report of the CTF [1] presented a draft set of bioinformatics core competencies, derived from the results of surveys of (1) core facility directors, (2) career opportunities, and (3) existing curricula. Since the publication of its 2014 report, the CTF has focused on the application of the guidelines in varied contexts to identify areas where refinement is needed. As a first step, the task force held an open meeting at the ISMB conference in July 2014. The ideas discussed at the meeting spawned four working groups (WGs), which focus on (i) defining core competencies for specific types and levels of bioinformatics training, (ii) mapping the curriculum guidelines and competencies to existing materials in order to identify the need for development of new materials, and (iii) identifying where revision of the guidelines may be valuable. The CTF is engaging the ISCB community through open WG meetings at ISCB’s official conferences. Thus far, the WGs have convened at the ISCB Great Lakes Bioinformatics Conference (Purdue University, May 2015) and at the ISMB/ECCB Conference (Dublin, Ireland, July 2015). Additionally, the CTF held a workshop at the Annual General Meeting of the Global Organization of Bioinformatics Learning, Education and Training (Cape Town, South Africa, November 2015). Specifically, the draft competencies have been employed in a wide range of activities and contexts (see Table 1 and [2–11]), including the development of new curricula, the analysis of existing curricula, and the creation of new roles involving bioinformatics. These activities have resulted in the identification of several areas where refinement would be useful: Table 1 Summary of the activities of the ISCB Curriculum Task Force. Identify different levels or phases of competency. It would be helpful to define different phases of competency development, or different levels of competency appropriate for distinct roles. Define competency profiles for disciplines that don’t fit into our current silos. Bioengineering provides an illustrative example of a discipline that requires core competency in bioinformatics but does not fit into our current categories. There are almost certainly others. It would be helpful if we could provide some guidance on how to produce ‘hybrid’ competency profiles, perhaps borrowing some competencies from the TF’s core set and others from different disciplines. The LifeTrain initiative (www.lifetrain.eu) [2, 3] is collecting competency profiles for a range of disciplines of relevance to the biomedical sciences and may provide a useful resource kit for this. Broaden the scope of the competency profiles in response to cutting-edge and emerging research. Current areas requiring improvement include incorporating competencies that capture a fundamental understanding of the biological principles central to analyzing biomolecular data, and broadening the user WG to include applications beyond medicine. Provide guidance on the evidence required to assess whether someone has acquired each competency. For undergraduate, Master’s and PhD programs, learning outcomes for each competency, perhaps with examples of appropriate means of assessment, would be valuable. For established professionals who need to assimilate competencies into their working lives, a different approach may be required (such as keeping a portfolio to capture evidence of competency); the CTF should seek guidance from relevant professional bodies, especially in regulated professions such as healthcare. Provide indicative course content or examples of programs that map to the competency requirements. We do not wish to prescribe what course providers should teach or how they should teach it; however, if a course provider is designing a course to meet a specific competency requirement, it may be helpful to find examples of other programs that do this successfully. One way of achieving this is by mapping existing training content to the TF’s competencies. Another way might be to provide an indication, perhaps based on several courses, of the course content that would meet the competency requirements. This would give course providers the freedom to build their own course syllabi without having to reinvent the wheel. Initiatives to collect examples of Creative Commons (or otherwise reusable) course materials will provide an extremely valuable bank of training materials that could be mapped to the core competencies.

MOTIVATION: Model selection and parameter inference are complex problems of long-standing interest in systems biology. Selecting between competing models arises commonly as underlying biochemical mechanisms are often not fully known, hence alternative models must be considered. Parameter inference yields important information on the extent to which the data and the model constrain parameter values. RESULTS: We report Dizzy-Beats, a graphical Java Bayesian evidence analysis tool implementing nested sampling - an algorithm yielding an estimate of the log of the Bayesian evidence Z and the moments of model parameters, thus addressing two outstanding challenges in systems modelling. A likelihood function based on the L1-norm is adopted as it is generically applicable to replicated time series data. AVAILABILITY AND IMPLEMENTATION: http://sourceforge.net/p/bayesevidence/home/Home/.

MOTIVATION: The Expectation-Maximization (EM) algorithm has been successfully applied to the problem of transcription factor binding site (TFBS) motif discovery and underlies the most widely used motif discovery algorithms. In the wider field of probabilistic modelling, the stochastic EM (sEM) algorithm has been used to overcome some of the limitations of the EM algorithm; however, the application of sEM to motif discovery has not been fully explored. RESULTS: We present MITSU (Motif discovery by ITerative Sampling and Updating), a novel algorithm for motif discovery, which combines sEM with an improved approximation to the likelihood function, which is unconstrained with regard to the distribution of motif occurrences within the input dataset. The algorithm is evaluated quantitatively on realistic synthetic data and several collections of characterized prokaryotic TFBS motifs and shown to outperform EM and an alternative sEM-based algorithm, particularly in terms of site-level positive predictive value. AVAILABILITY AND IMPLEMENTATION: Java executable available for download at http://www.sourceforge.net/p/mitsu-motif/, supported on Linux/OS X.