| The quantitative proteome of a human cell line M Beck, A Schmidt, J Malmstroem, M Claassen, A Ori, A Szymborska, ... Molecular systems biology 7 (1), 549, 2011 | 937 | 2011 |
| NASH limits anti-tumour surveillance in immunotherapy-treated HCC D Pfister, NG Núñez, R Pinyol, O Govaere, M Pinter, M Szydlowska, ... Nature 592 (7854), 450-456, 2021 | 850 | 2021 |
| Automated Gleason grading of prostate cancer tissue microarrays via deep learning E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ... Scientific reports 8 (1), 12054, 2018 | 403 | 2018 |
| Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability P Leuenberger, S Ganscha, A Kahraman, V Cappelletti, PJ Boersema, ... Science 355 (6327), eaai7825, 2017 | 386 | 2017 |
| Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry L Reiter, M Claassen, SP Schrimpf, M Jovanovic, A Schmidt, JM Buhmann, ... Molecular & Cellular Proteomics 8 (11), 2405-2417, 2009 | 361 | 2009 |
| False discovery rate estimation for cross-linked peptides identified by mass spectrometry T Walzthoeni, M Claassen, A Leitner, F Herzog, S Bohn, F Förster, M Beck, ... Nature methods 9 (9), 901-903, 2012 | 308 | 2012 |
| The Mtb proteome library: a resource of assays to quantify the complete proteome of Mycobacterium tuberculosis OT Schubert, J Mouritsen, C Ludwig, HL Röst, G Rosenberger, PK Arthur, ... Cell host & microbe 13 (5), 602-612, 2013 | 208 | 2013 |
| GM-CSF and CXCR4 define a T helper cell signature in multiple sclerosis E Galli, FJ Hartmann, B Schreiner, F Ingelfinger, E Arvaniti, M Diebold, ... Nature medicine 25 (8), 1290-1300, 2019 | 175 | 2019 |
| Nontargeted metabolomics reveals the multilevel response to antibiotic perturbations M Zampieri, M Zimmermann, M Claassen, U Sauer Cell reports 19 (6), 1214-1228, 2017 | 159 | 2017 |
| Estimation of absolute protein quantities of unlabeled samples by selected reaction monitoring mass spectrometry C Ludwig, M Claassen, A Schmidt, R Aebersold Molecular & Cellular Proteomics 11 (3), 2012 | 153 | 2012 |
| Sensitive detection of rare disease-associated cell subsets via representation learning E Arvaniti, M Claassen Nature communications 8 (1), 14825, 2017 | 148 | 2017 |
| Directed mass spectrometry: towards hypothesis-driven proteomics A Schmidt, M Claassen, R Aebersold Current opinion in chemical biology 13 (5-6), 510-517, 2009 | 116 | 2009 |
| Absolute quantification of microbial proteomes at different states by directed mass spectrometry A Schmidt, M Beck, J Malmström, H Lam, M Claassen, D Campbell, ... Molecular systems biology 7 (1), 510, 2011 | 115 | 2011 |
| Comprehensive proteomics M Beck, M Claassen, R Aebersold Current opinion in biotechnology 22 (1), 3-8, 2011 | 109 | 2011 |
| Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia S Kreutmair, S Unger, NG Núñez, F Ingelfinger, C Alberti, D De Feo, ... Immunity 54 (7), 1578-1593. e5, 2021 | 91 | 2021 |
| Structure-function relationships of HDL in diabetes and coronary heart disease M Cardner, M Yalcinkaya, S Goetze, E Luca, M Balaz, M Hunjadi, ... JCI insight 5 (1), 2020 | 82 | 2020 |
| The dynamics of root cap sloughing in Arabidopsis is regulated by peptide signalling CL Shi, D Von Wangenheim, U Herrmann, M Wildhagen, I Kulik, A Kopf, ... Nature plants 4 (8), 596-604, 2018 | 74 | 2018 |
| Landscape of exhausted virus-specific CD8 T cells in chronic LCMV infection I Sandu, D Cerletti, N Oetiker, M Borsa, F Wagen, I Spadafora, ... Cell Reports 32 (8), 2020 | 55 | 2020 |
| The SIB Swiss Institute of Bioinformatics’ resources: focus on curated databases SIB Swiss Institute of Bioinformatics Members Nucleic acids research 44 (D1), D27-D37, 2016 | 51 | 2016 |
| Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations on single cell data A Kopf, V Fortuin, VR Somnath, M Claassen PLoS computational biology 17 (6), e1009086, 2021 | 45 | 2021 |
