Hervé Ménager

Computational methods are central to the life sciences. The rapid growth and diversification of software tools and databases make it difficult to find, compare, and reuse methods for a given task. bio.tools is a community-driven registry designed to improve the visibility of research software and allow researchers to simplify access to the software ecosystem through structured, interoperable, and accessible metadata. Tools are annotated using the EDAM ontology and additional controlled vocabularies, enabling users to search and filter by scientific topics, operations, input/output data types, and data formats. bio.tools supports interactive exploration via rich tool landing pages and provides programmatic access through a documented API for search, retrieval, and registry statistics. The registry has expanded to almost 33,000 annotated tools through the combined contributions of thousands of community members and semi-automated literature mining that keep the registry up to date. Recent improvements to the registry include machine-assisted scoring to prioritise curator review, and consolidation of both its standards stack and software architecture. bio.tools has also become a foundational upstream metadata source that is reused by other services in the ELIXIR Research Software Ecosystem and beyond, to support synchronisation, cross-linking, and additional downstream services. bio.tools is freely available at https://bio.tools.

Identifying the most appropriate bioinformatics tool for a task remains challenging across multiple domains. Annotating tools with EDAM ontology terms (e.g. topics, operations, input / output data and formats) can help, but manual annotation is labour-intensive, error-prone, and difficult to scale, particularly given the high rate of first-time package developers in academic environments. At BioHackathon Europe 2025, our team explored how Large Language Models (LLMs) can assist this process through the Model Context Protocol (MCP), an emerging open standard that specifies how LLMs call external functions, using metabolomics as a domain use case. We developed an MCP-based workflow that grounds tool descriptions in the EDAM ontology (Ison et al., 2013), improving reproducibility and semantic precision. Two core modules, entry-point specification and semantic text segmentation, were completed during the hackathon, while additional mapping, validation, and reporting functions were outlined for follow-up development. Benchmarking integrated with the BioChatter framework (Lobentanzer et al., 2025) demonstrated that MCP-assisted models outperform unconstrained baselines on initial tests using metabolomics packages from bio.tools (Ison et al., 2019). Ongoing work will expand benchmarking datasets, refine term-mapping logic, and extend the workflow to proteomics, supporting scalable, ontology-driven annotation across the ELIXIR ecosystem.

The 26th annual Bioinformatics Open Source Conference (BOSC 2025, open-bio.org/events/bosc-2025) brought its community-driven focus on open-source bioinformatics and open science to the 2025 conference on Intelligent Systems for Molecular Biology and the European Conference on Computational Biology (ISMB/ECCB 2025). Since its launch in 2000, BOSC has been the premier annual meeting covering open-source bioinformatics and open science. Framed by two keynote addresses and a thought-provoking panel discussion, the two-day conference included sessions dedicated to open data, analytic tools and pipelines, workflow platforms, knowledge representation, and the application of AI/ML. The first keynote talk was delivered by Christine Orengo: “Working together to develop, promote and protect our data resources: Lessons learnt developing CATH and TED.” A joint session with the Bio-Ontologies and Knowledge Representation (BOKR) track the second day of BOSC started with a keynote talk by Chris Mungall entitled “Open Knowledge Bases in the Age of Generative AI”. A closing panel on Data Sustainability, moderated by Mónica Muñoz Torres, featured panelists Scott Edmunds, Varsha Khodiyar, Tony Burdett, Nicky Mulder, and Chris Mungall. This year, the CollaborationFest collaborative work event that typically precedes or follows ISMB was incorporated as part of the main conference and organized by BOSC with help from the Function and 3D-SIG tracks.

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

This project seeks to enhance the ELIXIR Research Software Ecosystem (RSEc) by increasing the findability, accessibility, interoperability, and reusability (FAIR principles) of Bioconductor’s extensive collection of over 2,000 bioinformatics packages. By aligning Bioconductor metadata with the EDAM ontology and integrating detailed package descriptions into the _bio.tools_ registry, we aim to improve the discoverability and usability of bioinformatics analysis tools. Short-term goals include mapping Bioconductor’s biocViews controlled vocabulary to EDAM concepts, developing a set of manually annotated “gold standard” packages, and evaluating tools for automated EDAM concept suggestions. Long-term, we intend to expand EDAM coverage across Bioconductor, phase out biocViews, and implement automated synchronisation with _bio.tools_. This initiative fosters collaboration between Bioconductor and ELIXIR, establishing a foundation for sustainable software management in European bioinformatics.Key results from the ELIXIR BioHackathon 2024 week include substantial progress in mapping the biocViews vocabulary to EDAM concepts, initiating the curation of a reference set of packages with manual annotations, integrating Bioconductor metadata into the ELIXIR Research Software Ecosystem (RSEc) with automated updates, and prototyping a tool for automated EDAM concept suggestions. Together, these achievements establish a strong foundation for further integration and refinement.

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 700 workflows registered.

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, the sample size required to detect additional variants using standard univariate association screening is increasingly prohibitive. Multi-trait GWAS offers a relevant alternative: it can improve statistical power and lead to new insights about gene function and the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been discussed, the strategy to select trait, among overwhelming possibilities, has been overlooked. In this study, we conducted extensive multi-trait tests using JASS (Joint Analysis of Summary Statistics) and assessed which genetic features of the analysed sets were associated with anincreased detection of variants as compared to univariate screening. Our analyses identified multiple factors associated with the gain in the association detection in multi-trait tests. Together, these factors of the analysed sets are predictive of the gain of the multi-trait test (Pearson’s ρ equal to 0.43 between the observed and predicted gain, P < 1.6 × 10 ^-60 ). Applying an alternative multi-trait approach (MTAG, multi-trait analysis of GWAS), we found that in most scenarios but particularly those with larger numbers of traits, JASS outperformed MTAG. Finally, we benchmark several strategies to select set of traits including the prevalent strategy of selecting clinically similar traits, which systematically underperformed selecting clinically heterogenous traits or selecting sets that issued from our data-driven models. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outline practical strategies for multi-trait testing.

Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles tailored for research software have been proposed by the FAIR for Research Software (FAIR4RS) Working Group. They provide a foundation for optimizing the reuse of research software. The FAIR4RS principles are, however, aspirational and do not provide practical instructions to the researchers. To fill this gap, we propose in this work the first actionable step-by-step guidelines for biomedical researchers to make their research software compliant with the FAIR4RS principles. We designate them as the FAIR Biomedical Research Software (FAIR-BioRS) guidelines. Our process for developing these guidelines, presented here, is based on an in-depth study of the FAIR4RS principles and a thorough review of current practices in the field. To support researchers, we have also developed a workflow that streamlines the process of implementing these guidelines. This workflow is incorporated in FAIRshare, a free and open-source software application aimed at simplifying the curation and sharing of FAIR biomedical data and software through user-friendly interfaces and automation. Details about this tool are also presented.

Here we report the results of a project started at the BioHackathon Europe 2022. Its goals were to cross-compare and analyze the metadata centralized in the Tools Ecosystem, and linked to the EDAM ontology, as well as to explore methods for connecting tools used in registered Galaxy workflows (i.e. WorkflowHub entries) to the annotations available in bio.tools.

Scientific software registries and repositories improve software findability and research transparency, provide information for software citations, and foster preservation of computational methods in a wide range of disciplines. Registries and repositories play a critical role by supporting research reproducibility and replicability, but developing them takes effort and few guidelines are available to help prospective creators of these resources. To address this need, the FORCE11 Software Citation Implementation Working Group convened a Task Force to distill the experiences of the managers of existing resources in setting expectations for all stakeholders. In this article, we describe the resultant best practices which include defining the scope, policies, and rules that govern individual registries and repositories, along with the background, examples, and collaborative work that went into their development. We believe that establishing specific policies such as those presented here will help other scientific software registries and repositories better serve their users and their disciplines.