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The 23rd annual Bioinformatics Open Source Conference (BOSC 2022) was part of this year’s conference on Intelligent Systems for Molecular Biology (ISMB). Launched in 2000 and held every year since, BOSC is the premier meeting covering open source bioinformatics and open science. ISMB 2022 was, for the first time, a hybrid conference, with the in-person component hosted in Madison, Wisconsin (USA). About 1000 people attended ISMB 2022 in person, with another 800 online. Approximately 200 people participated in BOSC sessions, which included 28 talks chosen from submitted abstracts, 46 posters, and a panel discussion, “Building and Sustaining Inclusive Open Science Communities”. BOSC 2022 included joint keynotes with two other COSIs. Jason Williams gave a BOSC / Education COSI keynote entitled "Riding the bicycle: Including all scientists on a path to excellence". A joint session with Bio-Ontologies featured a keynote by Melissa Haendel, “The open data highway: turbo-boosting translational traffic with ontologies.”

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

Author(s): Arkin, Adam P; Cottingham, Robert W; Henry, Christopher S; Harris, Nomi L; Stevens, Rick L; Maslov, Sergei; Dehal, Paramvir; Ware, Doreen; Perez, Fernando; Canon, Shane; Sneddon, Michael W; Henderson, Matthew L; Riehl, William J; Murphy-Olson, Dan; Chan, Stephen Y; Kamimura, Roy T; Kumari, Sunita; Drake, Meghan M; Brettin, Thomas S; Glass, Elizabeth M; Chivian, Dylan; Gunter, Dan; Weston, David J; Allen, Benjamin H; Baumohl, Jason; Best, Aaron A; Bowen, Ben; Brenner, Steven E; Bun, Christopher C; Chandonia, John-Marc; Chia, Jer-Ming; Colasanti, Ric; Conrad, Neal; Davis, James J; Davison, Brian H; DeJongh, Matthew; Devoid, Scott; Dietrich, Emily; Dubchak, Inna; Edirisinghe, Janaka N; Fang, Gang; Faria, Jose P; Frybarger, Paul M; Gerlach, Wolfgang; Gerstein, Mark; Greiner, Annette; Gurtowski, James; Haun, Holly L; He, Fei; Jain, Rashmi; Joachimiak, Marcin P; Keegan, Kevin P; Kondo, Shinnosuke; Kumar, Vivek; Land, Miriam L; Meyer, Folker; Mills, Marissa; Novichkov, Pavel S; Oh, Taeyun; Olsen, Gary J; Olson, Robert; Parrello, Bruce; Pasternak, Shiran; Pearson, Erik; Poon, Sarah S; Price, Gavin A; Ramakrishnan, Srividya; Ranjan, Priya; Ronald, Pamela C; Schatz, Michael C; Seaver, Samuel MD; Shukla, Maulik; Sutormin, Roman A; Syed, Mustafa H; Thomason, James; Tintle, Nathan L; Wang, Daifeng; Xia, Fangfang; Yoo, Hyunseung; Yoo, Shinjae; Yu, Dantong

The 22nd annual Bioinformatics Open Source Conference (BOSC 2021, open-bio.org/events/bosc-2021/) was held online as a track of the 2021 Intelligent Systems for Molecular Biology / European Conference on Computational Biology (ISMB/ECCB) conference. Launched in 2000 and held every year since, BOSC is the premier meeting covering topics related to open source software and open science in bioinformatics. In 2020, BOSC partnered with the Galaxy Community Conference to form the Bioinformatics Community Conference (BCC2020); that was the first BOSC to be held online. This year, BOSC returned to its roots as part of ISMB/ECCB 2021. As in 2020, the Covid-19 pandemic made it impossible to hold the conference in person, so ISMB/ECCB 2021 took place as an online meeting attended by over 2000 people from 79 countries. Nearly 200 people participated in BOSC sessions, which included 27 talks reviewed and selected from submitted abstracts, and three invited keynote talks representing a range of global perspectives on the role of open science and open source in driving research and inclusivity in the biosciences, one of which was presented in French with English subtitles.

Launched in 2000 and held every year since, the Bioinformatics Open Source Conference (BOSC) is a volunteer-run meeting coordinated by the Open Bioinformatics Foundation (OBF) that covers open source software development and open science in bioinformatics. Most years, BOSC has been part of the Intelligent Systems for Molecular Biology (ISMB) conference, but in 2018, and again in 2020, BOSC partnered with the Galaxy Community Conference (GCC). This year’s combined BOSC + GCC conference was called the Bioinformatics Community Conference (BCC2020, bcc2020.github.io). Originally slated to take place in Toronto, Canada, BCC2020 was moved online due to COVID-19. The meeting started with a wide array of training sessions; continued with a main program of keynote presentations, talks, posters, Birds of a Feather, and more; and ended with four days of collaboration (CoFest). Efforts to make the meeting accessible and inclusive included very low registration fees, talks presented twice a day, and closed captioning for all videos. More than 800 people from 61 countries registered for at least one part of the meeting, which was held mostly in the Remo.co video-conferencing platform.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

The Bioinformatics Open Source Conference is a volunteer-organized meeting that covers open source software development and open science in bioinformatics. Launched in 2000, BOSC has been held every year since. BOSC 2019, the 20th annual BOSC, took place as one of the Communities of Special Interest (COSIs) at the Intelligent Systems for Molecular Biology meeting (ISMB/ECCB 2019). The two-day meeting included a total of 46 talks and 55 posters, as well as eight Birds of a Feather interest groups. The keynote speaker was University of Cape Town professor Dr. Nicola Mulder, who spoke on “Building infrastructure for responsible open science in Africa”. Immediately after BOSC 2019, about 50 people participated in the two-day CollaborationFest (CoFest for short), an open and free community-driven event at which participants work together to contribute to bioinformatics software, documentation, training materials, and use cases.

Genome annotation is the process of identifying the location and function of a genome’s encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, Apollo is an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform.In this paper we first outline some of Apollo’s newer user interface features, which were driven by the needs of this expanding genomics community. These include support for real-time collaboration, allowing distributed users to simultaneously edit the same encoded features while also instantly seeing the updates made by other researchers on the same region in a manner similar to Google Docs. Its technical architecture enables Apollo to be integrated into multiple existing genomic analysis pipelines and heterogeneous laboratory workflow platforms. Finally, we consider the implications that Apollo and related applications may have on how the results of genome research are published and made accessible. Source: https://github.com/GMOD/ApolloLicense (BSD-3): https://github.com/GMOD/Apollo/blob/master/LICENSE.mdDocker: https://hub.docker.com/r/gmod/apollo/tags/, https://github.com/GMOD/docker-apolloRequirements: JDK 1.8, Node v6.0+User guide: http://genomearchitect.org; technical guide: http://genomearchitect.readthedocs.io/en/latest/Mailing list: apollo@lists.lbl.gov

National Institutes of Health (NIH), Monarch Initiative [OD #5R24OD011883]; Forums for Integrative Phenomics [U13 CA221044-01]; NCATS Data Translator [1OT3TR002019]; NCATS National Center for Digital Health Informatics Innovation [U24 TR002306];NIH Data Commons [1 OT3 OD02464-01 UNCCH]; Cost Action CA 16118 Neuro-MIG; British Heart Foundation Programme Grant [RG/13/5/30112]; Division of Intramural Research; NIAID; NIH; E-RARE project Hipbi-RD [01GM1608]; European Union's Horizon 2020 Research and Innovation Programme [779257]. Funding for open access charge: NIH; Donald A. Roux Family Fund (to P.N.R.). The Human Phenotype Ontology (HPO) - a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases - is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.

Genome-scale metabolic models (GEMs) generated from automated reconstruction pipelines often lack accuracy due to the need for extensive gapfilling and the inference of periphery metabolic pathways based on lower-confidence annotations. The central carbon pathways and electron transport chains are among the most well-understood regions of microbial metabolism, and these pathways contribute significantly toward defining cellular behavior and growth conditions. Thus, it is often useful to construct a simplified core metabolic model (CMM) that is comprised of only the high-confidence central pathways. In this chapter, we discuss methods for producing core metabolic models (CMM) based on genome annotations. With its reduced scope compared to GEMs, CMM reconstruction focuses on accurate representation of the central metabolic pathways related to energy biosynthesis and accurate energy yield predictions. We demonstrate the reconstruction and analysis of CMMs using the DOE Systems Biology Knowledgebase (KBase). The complete workflow is available at http://kbase.us/core-models/.

Computational methods for automated genome annotation are critical to our community's ability to make full use of the large volume of genomic sequence being generated and released. To explore the accuracy of these automated feature prediction tools in the genomes of higher organisms, we evaluated their performance on a large, well-characterized sequence contig from the Adh region ofDrosophila melanogaster. This experiment, known as the Genome Annotation Assessment Project (GASP), was launched in May 1999. Twelve groups, applying state-of-the-art tools, contributed predictions for features including gene structure, protein homologies, promoter sites, and repeat elements. We evaluated these predictions using two standards, one based on previously unreleased high-quality full-length cDNA sequences and a second based on the set of annotations generated as part of an in-depth study of the region by a group ofDrosophila experts. Although these standard sets only approximate the unknown distribution of features in this region, we believe that when taken in context the results of an evaluation based on them are meaningful. The results were presented as a tutorial at the conference on Intelligent Systems in Molecular Biology (ISMB-99) in August 1999. Over 95% of the coding nucleotides in the region were correctly identified by the majority of the gene finders, and the correct intron/exon structures were predicted for >40% of the genes. Homology-based annotation techniques recognized and associated functions with almost half of the genes in the region; the remainder were only identified by the ab initio techniques. This experiment also presents the first assessment of promoter prediction techniques for a significant number of genes in a large contiguous region. We discovered that the promoter predictors' high false-positive rates make their predictions difficult to use. Integrating gene finding and cDNA/EST alignments with promoter predictions decreases the number of false-positive classifications but discovers less than one-third of the promoters in the region. We believe that by establishing standards for evaluating genomic annotations and by assessing the performance of existing automated genome annotation tools, this experiment establishes a baseline that contributes to the value of ongoing large-scale annotation projects and should guide further research in genome informatics.

Computational biology comprises a wide range of different technologies and approaches. In order to combine different technologies to create more powerful workflows, multiple individuals and research groups generally need to collaborate. The format of data exchanged, the biology behind that data, and the individuals contributing the data or providing tools for its interpretation need to find mutual understanding and consensus. Much conversation and joint investigation are required in order to identify and implement the best approach to using and combining the latest technologies. Traditionally, scientific conferences feature talks that present novel technologies or insights, followed up by informal discussions during coffee breaks - not necessarily involving the presenting party. In multi-institution collaborations, in order to reach agreement on implementation details or to transfer deeper insights in a technology and practical skills, a representative of one collaborating research group typically visits the other. However, this does not scale well when the number of technologies or research groups is large. Conferences have responded to this issue by introducing Birds-of-a-Feather (BoF) sessions, which offer an opportunity for individuals sharing interests, commonly with prior acquaintance on mailing lists, to intensify their interaction. However, parallel BoF sessions often make it hard for participants to join multiple BoFs and find common ground between the different technologies. Also, industrial participants in these discussions are rare, since their focus is on selling a product, not in forming collaborations that may not be immediately profitable. We here summarise our experience with Codefests, Hackathons and Sprints, which are interactive developer meetings in our field that aim to reduce the limitations of traditional scientific meetings described above, by strengthening the interaction among peers and letting the participants determine the schedule and topics covered at the meeting. These meetings are commonly run as loosely scheduled “unconferences� (self-organized identification of participants and topics for meetings) over at least two days, with early introductory talks to welcome and schedule contributors, followed by intensive collaborative coding sessions. We describe some differences in the way these meetings are organised, the audience is addressed, and in their outreach to their respective communities. The most prominent achievements of those meetings are summarised. Hackathons, Codefests and Springs share a stimulating atmosphere that encourages participants to jointly brainstorm and tackle problems of shared interest in a selfdriven proactive environment.

In July 2013, more than 100 bioinformatics researchers, developers and users of Open Source Software gathered in Berlin, Germany, to attend the 14th Annual Bioinformatics Open Source Conference (BOSC, http://www.open-bio.org/wiki/BOSC_2013, Harris et al., 2013). Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community, and a focused environment for developers and users to interact and share ideas about standards, software development practices and practical techniques for solving bioinformatics problems. BOSC includes a 2 day ‘CodeFest’ preceding the formal conference, which provides a venue for developers to meet in person to work on or plan joint projects (Moller et al., 2013). The session topics at BOSC 2013 included Cloud and Parallel Computing, Visualization, Software Interoperability, Genome-scale Data Management, a session for updates on ongoing Open Source projects and two new sessions: Open Science and Reproducible Research and Translational Bioinformatics, recognizing the growing use of computational biology in medical applications. Slides from all of the presentations are available on the BOSC Web site, along with some of the posters and video recordings for selected talks, including the keynotes and panel discussion. Open Science is a movement dedicated to making all aspects of scientific knowledge production freely available for reuse and extension, including scientific data, methods and analyses. In response to the increasing traction that this movement has gained, BOSC 2013 featured a new session devoted explicitly to Open Science. One of the objectives of Open Science is the wider issue of making published research reproducible. Aside from openness in software licensing, this also includes openness of data and unhindered access to scientific papers themselves (Open Access). When researchers can freely access publications and the source code and data that support them, it becomes possible for them to recreate the steps that the authors went through to reach their conclusions and to then go beyond them. In this way, Open Science not only stands to provide the value of validating published results by recreating them but also to accelerate the pace of scientific discovery, by enabling researchers to more effectively build on the results of previous work, rather than having to reinvent tools and reassemble datasets. Each day of BOSC traditionally starts off with a keynote talk by a person of influence in Open Source bioinformatics. BOSC 2013’s first keynote speaker was Cameron Neylon, the Advocacy Director for the Public Library of Science, who is a prominent advocate for open science. Neylon discussed the cultural issues that are hindering open science, and spoke about the potential of openness in scientific collaborations for generating impact. Our second keynote speaker was Sean Eddy, a group leader at the Howard Hughes Medical Institute's Janelia Farm, who is perhaps best known as the author of the HMMER software suite (Eddy, 2011). He discussed how his own experience and practices show that dedicating effort to thorough engineering in tool development—which is often shunned as uninteresting and unpublishable—can be a key to creating a lasting impact. To stimulate discussion on controversial or multifaceted topics, BOSC includes a panel, in which panelists representing a range of viewpoints, answer questions from the audience. This year’s panel was on Strategies for Funding and Maintaining Open Source Software. To secure continued funding for a software project, researchers must be able to demonstrate its impact. The panelists explored ways to quantify usage of one’s software as a measure of impact. They agreed that traditional publications, and tracking their citations, still play an important role in publicizing and demonstrating the use of one’s software, but they are not the only metric. With the increasing reliance of more and more fields of biology on computational tools to manage and analyze their data, BOSC seems assured to stay relevant to life science, and thus to life scientists. Additional Information Plan to join us for BOSC: 15th Annual Bioinformatics Open Source Conference in Boston, USA, July 11–12, 2014. For more information visit http://www.open-bio.org/wiki/BOSC_2014.

We present enhancements to the Compass algorithm that automatically deduce interchemotype relationships and generate predictive quantitative models of receptor binding based solely on structure-activity data. We applied the technique to a series of compounds assayed for 5-HT 1A binding. A model was constructed from 20 compounds of two chemotypes and used to predict the affinities and bioactive conformation of 35 new compounds, most of which had new underlying scaffolds and/or functional groups. The model's mean error of prediction was 0.5 log units (essentially the assay resolution), even on quite divergent series. The predictions are supported by an interpretable hypothesis for the binding determinants of the receptor and the geometric relationships of the chemotypes

The fly Drosophila melanogaster is one of the most intensively studied organisms in biology and serves as a model system for the investigation of many developmental and cellular processes common to higher eukaryotes, including humans. We have determined the nucleotide sequence of nearly all of the ∼120-megabase euchromatic portion of the Drosophila genome using a whole-genome shotgun sequencing strategy supported by extensive clone-based sequence and a high-quality bacterial artificial chromosome physical map. Efforts are under way to close the remaining gaps; however, the sequence is of sufficient accuracy and contiguity to be declared substantially complete and to support an initial analysis of genome structure and preliminary gene annotation and interpretation. The genome encodes ∼13,600 genes, somewhat fewer than the smaller Caenorhabditis elegans genome, but with comparable functional diversity.

In this postgenomic era, it is no longer necessary to argue the need for automated methods for sequence annotation. Many researchers have designed tools for analyzing DNA sequences, but running multiple tools and interpreting the results can be tedious and confusing. In the last few years, many analysis workbenches have been developed to help streamline the process of sequence annotation. Genotator, developed in 1996, is still a popular choice owing to its ease of use and its configurability. This article will review annotating sequence data using the Genotator.

Publisher Summary There exists a sequence of 8 nucleotides, highly conserved at the boundary between an exon and an intron, referred to as the 5′ splice site (5′ ss). The boundary between an intron and an exon, the 3′ splice site (3′ ss), also exhibits a highly conserved sequence of 4 nucleotides, preceded by a pyrimidine-rich region. To interpret the deluge of sequence information generated by the human genome project, it is important to be able to identify genes in uncharacterized sequences. Without this capability, the sequence information is of little value. For each sequence in GenBank, the splice sites were located using the information in the annotation preceding the sequence, a FEATURES line being followed by multiple lines indicating different features present in the gene. The percentages of lariat windows with high-scoring branch point sequences in all GenBank categories, with the exception of viruses, are higher than those of random sequences. A notable observation is that even the window that contains the second highest frequency of branch points among the five windows analyzed always had a lower frequency of high scoring branch points than expected for a window with a random sequence.

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects.

An intermediate stage in the process of eukaryotic RNA splicing is the formation of a lariat structure. It is anchored at an adenosine residue in intron between 10 and 50 nucleotides upstream of the 3' splice site. A short conserved sequence (the branch point sequence) functions as the recognition signal for the site of lariat formation. It has been generally assumed that the branch point is recognized mainly by the presence of its unique sequence where the lariat is formed. However, the known branch point consensus sequence is found to be distributed nearly randomly throughout the gene sequence with only a slightly higher frequency in the expected lariat region. Further, the known consensus sequence is found to be clearly inadequate to specify branch points. These observations have implications for understanding the mechanism of branch point recognition in the process of splicing, and the possible evolution of the branch point signal.