Abstract. Summary: Mass spectrometry (MS) is a cornerstone technology in modern molecular biology, powering diverse applications across proteomics, metabol

The ELIXIR BioHackathon Europe took place 3–7 November 2025 in Bad Saarow near Berlin. Among the ~30 Projects was the “Metabolomics and proteomics file format interoperability fest”, co-organised by S...

High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing data set scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and streamlined workflows. Since its introduction in 2005, the xcms R package has become one of the most widely used tools for LC-MS data preprocessing. Developed through an open-source, community-driven approach, xcms maintains long-term stability while continuously expanding its capabilities and accessibility. We present recent advancements that position xcms as a central component of a modular and interoperable software ecosystem for metabolomics data analysis. Key improvements include enhanced scalability, enabling the processing of large-scale experiments with thousands of samples on standard computing hardware. These developments empower users to build comprehensive, customizable, and reproducible workflows tailored to diverse experimental designs and analytical needs. An expanding collection of tutorials, documentation, and teaching materials further supports both new and experienced users in leveraging broader R and Bioconductor ecosystems. These resources facilitate the integration of statistical modeling, visualization tools, and domain-specific packages, extending the reach and impact of xcms workflows. Together, these enhancements solidify xcms as a cornerstone of modern metabolomics research.

There are many opportunities to join community meetings, subcommittees and debriefing sessions. Find links to them on this Etherpad, and subscribe to the Google calendar below or use this ics feed to…

A blog for the Bioconductor community!

Abstract. The Reactome Knowledgebase (https://reactome.org) is a freely accessible, expert-curated, open-source, and open-data resource that describes huma

Abstract. Enzymes are the molecular machines of life and play an indispensable role in numerous biotechnological and biomedical applications. Despite the a

Abstract. The open spectral library MassBank (https://massbank.jp/) started in 2006 in Japan, as one of the first open source and open access cross-vendor

A goal of multiomics experiments is to understand how mechanistic molecular biology is altered between conditions, typically a control group and experimental groups. Oftentimes, this involves studying...

Untargeted LC–MS metabolomics generates large, noisy datasets that demand complex, parameter-intensive workflows across multiple software tools. While over 5000 metabolomics datasets are available in ...

This tutorial offers a step-by-step guide for analytical chemists to train machine learning models for MS-based metabolomics. It covers data preparation, feature engineering, model selection, evaluati...

The rise of data-driven science has made research data management (RDM) essential, yet implementing it remains complex due to diverse disciplinary needs, limited tailored guidance, and gaps in trainin...

The Bioconductor Code of Conduct Committee updates, disseminates, upholds and enforces the Code of Conduct (http://bioconductor.org/about/code-of-conduct/) across all platforms of the Bioconductor…

Supplementary materials that accompany scientific articles enhance transparency, reproducibility and scientific impact. This study presents FAIR-SMART, a tool that enables computational access to thes...

Mass spectrometry-based lipidomics and metabolomics generate large, complex datasets requiring effective analysis. Here, authors review key statistical and visualization methods alongside widely used R and Python tools, and provide a GitBook with step-by-step code for accessible, reproducible data analysis.

Advances in mass spectrometry (MS) instrumentation, including higher resolution, faster scan speeds, and improved sensitivity, have dramatically increased the data volume and complexity. The adoption ...

Release Notes for Cytoscape

Over the past decades, mass spectrometry has served as a fundamental technique for molecular identification in the field of metabolomics, widely applied to the analysis and characterization of biomole...

The construction of multicellular mechanistic models in systems biology typically requires months of literature research, programming expertise, and deep knowledge of specialized computational tools. ...