%0 Journal Article
%A Mehta, Subina
%A Bernt, Matthias
%A Chambers, Matthew
%A Fahrner, Matthias
%A Föll, Melanie Christine
%A Gruening, Bjoern
%A Horro, Carlos
%A Johnson, James E
%A Loux, Valentin
%A Rajczewski, Andrew T
%A Schilling, Oliver
%A Vandenbrouck, Yves
%A Gustafsson, Ove Johan Ragnar
%A Thang, W C Mike
%A Hyde, Cameron
%A Price, Gareth
%A Jagtap, Pratik D
%A Griffin, Timothy J
%T A Galaxy of informatics resources for MS-based proteomics.
%J Expert review of proteomics
%V 20
%N 11
%@ 1478-9450
%C Abingdon
%I Taylor & Francis Group
%M DKFZ-2023-01999
%P 251-266
%D 2023
%Z 2023 Jul-Dec;20(11):251-266
%X Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization, and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting analysis requirements of increasingly complex MS-based proteomic data, and associated multi-omic data, are critically needed. These requirements included availability of software spanning diverse types of analyses, along with scalability for large-scale, compute-intensive applications and mechanisms to ease adoption of the software.The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses.The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.
%K Bioinformatics (Other)
%K Computational workflows (Other)
%K Galaxy platform (Other)
%K Mass-spectrometry (Other)
%K Multi-omics (Other)
%K Reproducibility (Other)
%K proteomics (Other)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:37787106
%R 10.1080/14789450.2023.2265062
%U https://inrepo02.dkfz.de/record/284410