Meetings

Recent preprints

• May 20, 2026

  INTOXICOM Workshop Report: Systems Biology Models for Toxicology

  This report summarizes the ELIXIR Toxicology Community workshop on Systems Biology Models for Toxicology, held on 11–12 September 2025 in Athens, Greece. The workshop tookplace under the INTOXICOM Implementation Study workshop series (Integrating the toxicology community into ELIXIR 2024) and aimed to strengthen connections between systems biologyand toxicology by bridging ELIXIR resources with systems toxicology modelling approaches usedfor chemical risk assessment. The workshop explored the role of qualitative and quantitative exposure–health outcome models, including (quantitative) Adverse Outcome Pathways ((q)-AOPs), AOP networks, and mechanistic toxicology models. Participants examined two usecases focused on neurotoxicity and endocrine disruption, discussing how ELIXIR tools, platforms,core data resources, and modelling environments can support them. The workshop concluded with a discussion on a roadmap for integrating ELIXIR systems biology infrastructures and tools into applied systems toxicology. This report documents the presentations, discussions, and practical results that contribute to Deliverables of INTOXICOM WP5. less than 1 minute read
• May 1, 2026

  INTOXICOM Workshop Report: Advancing FAIR toxicology research output across Europe: ELIXIR & FAIRsharing studies

  As part of the INTOXICOM Implementation Study for the ELIXIR Toxicology Community a series of workshops is organized. The first INTOXICOM workshop was held in May 2024. Here, we here report on the 2nd workshop, titled “Enhancing Research Output: FAIR documentation and Tool Management for toxicology studies” which was held from 27 to 28 November 2024 at the Main Building of the University of Basel in Switzerland less than 1 minute read
• Apr 27, 2026

  Snakemake Hackathon 2026

  Reproducible, scalable, and portable data-analysis pipelines are now a fundamental prerequisite for modern data analysis research across all research domains. Snakemake has emerged as one of the most widely adopted systems for declarative pipeline orchestration, combining a concise Python-based DSL with native support for containers, cloud back-ends, and fine-grained provenance tracking, and it underpins thousands of published studies. Nonetheless, the platform’s continued evolution faces several open challenges: improving core performance on heterogeneous high-performance-computing (HPC) resources, extending the plugin architecture for domain-specific extensions, and lowering the entry barrier for novice users while preserving full reproducibility.Here we report on the Snakemake Hackathon 2026, convened in Munich, Germany (9–13 March 2026) with more than 40 participants representing academia, industry, and national-level research infrastructure. less than 1 minute read
• Apr 14, 2026

  Improving package annotation in metabolomics and proteomics via robust, ontology-driven LLM integration

  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. 1 minute read
• Apr 13, 2026

  GA4GH VRS for the Semantic Web

  There is currently no standardized representation of genomic variants in RDF. To address this issue, during the DBCLS BioHackathon 2024 we modelled an RDF Schema for the GA4GH VRS to enable interoperability of this standard within the bioinformatics semantic web community. less than 1 minute read
• Apr 10, 2026

  Minimal information standardization of phenomic experimental data in animals

  The current landscape of animal phenomics is characterised by a substantial lack of standardisation, hindering data reuse, reproducibility, and interoperability across studies, all of which are particularly important in light of the 3Rs principles for animal experiments (replace, reduce, refine). Within ELIXIR, the Domestic Animals Genome and Phenome Focus Group emerged to establish standardised practices that enhance the quality and interoperability of animal research data. In this context, the ISA model presents a robust, domain-agnostic framework well-established in the life sciences for describing experimental metadata. Notably, other scientific communities, such as the ELIXIR Plant and Metabolomics Communities (MIAPPE, PhenoMeNal), have successfully leveraged the ISA model to improve the consistency and usability of their metadata. Our project aims to develop a minimal information checklist tailored specifically for phenomics, facilitating the integration of diverse datasets, including recirculation systems in agriculture, and fostering collaborative research efforts. We will focus on various goals.Identifying essential aspects of animal phenotyping, informed by existing frameworks and community input. We aim to produce a concise and practical checklist that can be readily adopted by researchers, and promote a culture of standardisation.Mapping the checklist to the ISA model ensures alignment with established standards, promotes interoperability and facilitates data reuse while improving the overall quality of research outputs. Adopting existing ISA tools streamlines the implementation of our metadata checklist, providing user-friendly interfaces for researchers to manage, document, and share animal phenotyping data efficiently. 1 minute read
• Mar 31, 2026

  Evolving FAIR Image Analysis in Galaxy for Cross-domain and AI-ready Applications

  The increasing adoption of image-based technologies across life sciences, environmental research, and related domains has increased the demand for interoperable, reproducible, and FAIR-compliant image analysis infrastructures. At ELIXIR BioHackathon Europe 2025, Project 9, “Evolving FAIR Image Analysis in Galaxy for Cross-domain and AI-ready Applications”, addressed these challenges by enhancing the Galaxy platform for bioimage analysis with a focus on semantic interoperability, content-based reproducibility validation, and user-centered onboarding tutorials.To advance semantic interoperability, we developed a curated vocabulary based on the EDAM Bioimaging ontology, which was applied to annotate tutorials on the Galaxy Training Network, improving discoverability and aligning with evolving community standards. For reproducibility and AI-readiness, we integrated the International Standard Content Code (ISCC) via the ISCC-SUM tool suite, enabling format-independent content-based validation, dataset deduplication, and assessment of data similarity for robust model training. Finally, usability improvements included a comprehensive onboarding tutorial for newcomers, enhanced integration with OMERO and BioImage Archive, and generally improved tool interoperability, including support for GeoJSON-based spatial annotations. Collectively, these developments establish a scalable, cross-domain image analysis framework within Galaxy, promoting FAIR-aligned practices while enabling reproducible and AI-ready workflows. 1 minute read