Nucleic Acids Research· 2025Q1
The ProteomeXchange consortium in 2026: making proteomics data FAIR
- 62citations
- Q1SCImago
- 2025year
Short summary
ProteomeXchange has accelerated data submission, with 30,097 datasets added in the last 3 years, totaling 64,330 by June 2025, and has improved support for data standards and increased data reuse.
AI-generated from the title and abstract; the full text is not read.
Key points
- ProteomeXchange received 30,097 new datasets between mid-2022 and June 2025, contributing to a total of 64,330 submitted datasets.
- Improvements have been made to support Proteomics Standards Initiative standards, including Universal Spectrum Identifiers and SDRF-Proteomics.
- Data reuse has increased, with public datasets being reanalyzed and used for novel machine learning approaches.
- Future developments will focus on controlled-access human proteomics data and non-MS proteomics methods.
AI-generated from the title and abstract; the full text is not read.
Abstract
The ProteomeXchange consortium of proteomics resources (http://www.proteomexchange.org) was established to standardize open data practices in the mass spectrometry (MS)-based proteomics field. Here, we describe the main developments in ProteomeXchange in the last 3 years. The six member databases of ProteomeXchange, spread out in three different continents, are the PRIDE database, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public. We provide updated data submission statistics, showcasing that the number of datasets submitted to ProteomeXchange resources has continued to accelerate every year. Through June 2025, 64 330 datasets had been submitted to ProteomeXchange resources, and from those, 30 097 (47%) just in the last 3 years. We also report on the improvements in the support for the standards developed by the Proteomics Standards Initiative, e.g. for Universal Spectrum Identifiers and for SDRF (Sample and Data Relationship Format)-Proteomics. Additionally, we highlight the increase in data reuse activities of public datasets, including targeted reanalyses of datasets of different proteomics data types, and the development of novel machine learning approaches. Finally, we summarize our plans for the near future, covering the development of resources for controlled-access human proteomics data, and for the support of non-MS proteomics approaches.
The authors' abstract, as published at the source. Nucleic Acids Research, 2025 · DOI ↗
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Field: Spectroscopy
SpectroscopyChemistry