DOE OSTI · 2574496
Open-Source and FAIR Research Software for Proteomics
Abstract
Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.
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Perez-Riverol, Yasset [European Bioinformatics Institute, Cambridge (United Kingdom). European Molecular Biology Laboratory] (ORCID:0000000165796941), Bittremieux, Wout [Univ. of Antwerp (Belgium)] (ORCID:0000000231051359), Noble, William S. [Univ. of Washington, Seattle, WA (United States)] (ORCID:0000000172834715), Martens, Lennart [VIB-UGent Center for Medical Biotechnology, Ghent (Belgium); Ghent Univ. (Belgium)] (ORCID:000000034277658X), Bilbao, Aivett [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory (EMSL); USDOE Agile BioFoundry, Emeryville, CA (United States)] (ORCID:0000000329858249), Lazear, Michael R. [Belharra Therapeutics, San Diego, CA (United States)] (ORCID:0000000153134262), Grüning, Bjorn [Albert-Ludwigs University, Freiburg (Germany)] (ORCID:0000000230796586), Katz, Daniel S. [Univ. of Illinois at Urbana-Champaign, IL (United States). National Center for Supercomputing Applications (NCSA)] (ORCID:0000000159347525), MacCoss, Michael J. [Univ. of Washington, Seattle, WA (United States)] (ORCID:0000000318530256), Dai, Chengxin [Beijing Institute of Life Omics (China). National Center for Protein Sciences], Eng, Jimmy K. [Univ. of Washington, Seattle, WA (United States)] (ORCID:0000000163526737), Bouwmeester, Robbin [VIB-UGent Center for Medical Biotechnology, Ghent (Belgium); Ghent Univ. (Belgium)] (ORCID:0000000168077029), Shortreed, Michael R. [Univ. of Wisconsin, Madison, WI (United States)] (ORCID:0000000346260863), Audain, Enrique [Carl von Ossietzky University, Oldenburg (Germany). University Medicine Oldenburg], Sachsenberg, Timo [University of Tübingen (Germany)] (ORCID:0000000228336070), Van Goey, Jeroen [InstaDeep London (United Kingdom)], Wallmann, Georg [Max Planck Institute of Biochemistry, Martinsried (Germany)], Wen, Bo [Univ. of Washington, Seattle, WA (United States)], Käll, Lukas [KTH Royal Inst. of Technology, Stockholm (Sweden). Science for Life Laboratory] (ORCID:0000000156899797), Fondrie, William E. [Talus Bioscience, Seattle, WA (United States)] (ORCID:0000000215543716). 2025-04-23. Open-Source and FAIR Research Software for Proteomics. https://doi.org/10.1021/acs.jproteome.4c01079
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