A 2025 perspective on the role of machine learning for biomarker discovery in clinical proteomics

Source
Expert review of proteomics - ISSN 1478-9450- (2025) p. 1-12

A universal language for finding mass spectrometry data patterns

Source
Nature methods - ISSN 1548-7091-22:6 (2025) p. 1247-1254
Author(s)
    Tito Damiani, Alan K. Jarmusch, Allegra T. Aron, Daniel Petras, Vanessa V. Phelan, Haoqi Nina Zhao, Wout Bittremieux, Deepa D. Acharya, Mohammed M.A. Ahmed, Anelize Bauermeister, Matthew J. Bertin, Paul D. Boudreau, Ricardo M. Borges, Benjamin P. Bowen, Christopher J. Brown, Fernanda O. Chagas, Kenneth D. Clevenger, Mario S.P. Correia, William J. Crandall, Max Crüsemann, Eoin Fahy, Oliver Fiehn, Neha Garg, William H. Gerwick, Jeffrey R. Gilbert, Daniel Globisch, Paulo Wender P. Gomes, Steffen Heuckeroth, C. Andrew James, Scott A. Jarmusch, Sarvar A. Kakhkhorov, Kyo Bin Kang, Nikolas Kessler, Roland D. Kersten, Hyunwoo Kim, Riley D. Kirk, Oliver Kohlbacher, Eftychia E. Kontou, Ken Liu, Itzel Lizama-Chamu, Gordon T. Luu, Tal Luzzatto Knaan, Helena Mannochio-Russo, Michael T. Marty, Yuki Matsuzawa, Andrew C. McAvoy, Laura-Isobel McCall, Osama G. Mohamed, Omri Nahor, Mingxun Wang

Improved open modification searching via unified spectral search with predicted libraries and enhanced vector representations in ANN-SoLo

Source
Zenodo, 2025,
Author(s)

Self-supervised learning from small-molecule mass spectrometry data

Source
Nature biotechnology - ISSN 1087-0156- (2025) p.
Author(s)