| Mass-spectrometry-based draft of the human proteome M Wilhelm, J Schlegl, H Hahne, AM Gholami, M Lieberenz, MM Savitski, ... Nature 509 (7502), 582-587, 2014 | 1888 | 2014 |
| The target landscape of clinical kinase drugs S Klaeger, S Heinzlmeir, M Wilhelm, H Polzer, B Vick, PA Koenig, ... Science 358 (6367), eaan4368, 2017 | 609 | 2017 |
| Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning S Gessulat, T Schmidt, DP Zolg, P Samaras, K Schnatbaum, J Zerweck, ... Nature methods 16 (6), 509-518, 2019 | 435 | 2019 |
| A deep proteome and transcriptome abundance atlas of 29 healthy human tissues D Wang, B Eraslan, T Wieland, B Hallström, T Hopf, DP Zolg, J Zecha, ... Molecular systems biology 15 (2), e8503, 2019 | 409 | 2019 |
| A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets [S] MM Savitski, M Wilhelm, H Hahne, B Kuster, M Bantscheff Molecular & Cellular Proteomics 14 (9), 2394-2404, 2015 | 320 | 2015 |
| Global proteome analysis of the NCI-60 cell line panel AM Gholami, H Hahne, Z Wu, FJ Auer, C Meng, M Wilhelm, B Kuster Cell reports 4 (3), 609-620, 2013 | 309 | 2013 |
| Mass-spectrometry-based draft of the Arabidopsis proteome J Mergner, M Frejno, M List, M Papacek, X Chen, A Chaudhary, ... Nature 579 (7799), 409-414, 2020 | 233 | 2020 |
| ProteomicsDB T Schmidt, P Samaras, M Frejno, S Gessulat, M Barnert, H Kienegger, ... Nucleic Acids Research, 2017 | 178 | 2017 |
| Building ProteomeTools based on a complete synthetic human proteome DP Zolg, M Wilhelm, K Schnatbaum, J Zerweck, T Knaute, B Delanghe, ... Nature methods 14 (3), 259-262, 2017 | 178 | 2017 |
| ProteomicsDB: a multi-omics and multi-organism resource for life science research P Samaras, T Schmidt, M Frejno, S Gessulat, M Reinecke, A Jarzab, ... Nucleic acids research 48 (D1), D1153-D1163, 2020 | 129 | 2020 |
| The emerging landscape of single-molecule protein sequencing technologies JA Alfaro, P Bohländer, M Dai, M Filius, CJ Howard, XF Van Kooten, ... Nature methods 18 (6), 604-617, 2021 | 127 | 2021 |
| Optimized chemical proteomics assay for kinase inhibitor profiling G Médard, F Pachl, B Ruprecht, S Klaeger, S Heinzlmeir, D Helm, H Qiao, ... Journal of proteome research 14 (3), 1574-1586, 2015 | 123 | 2015 |
| Generating high quality libraries for DIA MS with empirically corrected peptide predictions BC Searle, KE Swearingen, CA Barnes, T Schmidt, S Gessulat, B Küster, ... Nature communications 11 (1), 1548, 2020 | 121 | 2020 |
| Meltome atlas—thermal proteome stability across the tree of life A Jarzab, N Kurzawa, T Hopf, M Moerch, J Zecha, N Leijten, Y Bian, ... Nature methods 17 (5), 495-503, 2020 | 116 | 2020 |
| Ion mobility tandem mass spectrometry enhances performance of bottom-up proteomics D Helm, JPC Vissers, CJ Hughes, H Hahne, B Ruprecht, F Pachl, A Grzyb, ... Mol Cell Proteomics, 2014 | 105 | 2014 |
| Peptide level turnover measurements enable the study of proteoform dynamics J Zecha, C Meng, DP Zolg, P Samaras, M Wilhelm, B Kuster Molecular & Cellular Proteomics 17 (5), 974-992, 2018 | 89 | 2018 |
| Mining the human tissue proteome for protein citrullination CY Lee, D Wang, M Wilhelm, DP Zolg, T Schmidt, K Schnatbaum, ... Molecular & Cellular Proteomics 17 (7), 1378-1391, 2018 | 78 | 2018 |
| ProteomeTools: Systematic characterization of 21 post-translational protein modifications by liquid chromatography tandem mass spectrometry (LC-MS/MS) using synthetic peptides DP Zolg, M Wilhelm, T Schmidt, G Médard, J Zerweck, T Knaute, ... Molecular & Cellular Proteomics 17 (9), 1850-1863, 2018 | 66 | 2018 |
| Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics M Wilhelm, DP Zolg, M Graber, S Gessulat, T Schmidt, K Schnatbaum, ... Nature communications 12 (1), 3346, 2021 | 52 | 2021 |
| mz5: space-and time-efficient storage of mass spectrometry data sets M Wilhelm, M Kirchner, JAJ Steen, H Steen Molecular & Cellular Proteomics 11 (1), 2012 | 52 | 2012 |
Bernhard KusterProfessor for Proteomics and BioanalyticsПотвърден имейл адрес: tum.de
