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 | 721 | 2019 |
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 | 389 | 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 | 268 | 2021 |
ProteomicsDB T Schmidt, P Samaras, M Frejno, S Gessulat, M Barnert, H Kienegger, ... Nucleic Acids Research, 2017 | 227 | 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 | 192 | 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 | 189 | 2020 |
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 | 140 | 2021 |
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 | 120 | 2018 |
A proteomics sample metadata representation for multiomics integration and big data analysis C Dai, A Füllgrabe, J Pfeuffer, EM Solovyeva, J Deng, P Moreno, ... Nature Communications 12 (1), 5854, 2021 | 62 | 2021 |
Proteome activity landscapes of tumor cell lines determine drug responses M Frejno, C Meng, B Ruprecht, T Oellerich, S Scheich, K Kleigrewe, ... Nature communications 11 (1), 3639, 2020 | 61 | 2020 |
Challenges in clinical metaproteomics highlighted by the analysis of acute leukemia patients with gut colonization by multidrug-resistant enterobacteriaceae J Rechenberger, P Samaras, A Jarzab, J Behr, M Frejno, A Djukovic, ... Proteomes 7 (1), 2, 2019 | 60 | 2019 |
ProteomicsDB: toward a FAIR open-source resource for life-science research L Lautenbacher, P Samaras, J Muller, A Grafberger, M Shraideh, J Rank, ... Nucleic Acids Research 50 (D1), D1541-D1552, 2022 | 39 | 2022 |
Decrypting drug actions and protein modifications by dose-and time-resolved proteomics J Zecha, FP Bayer, S Wiechmann, J Woortman, N Berner, J Müller, ... Science 380 (6640), 93-101, 2023 | 38 | 2023 |
Mass spectrometry-based draft of the mouse proteome P Giansanti, P Samaras, Y Bian, C Meng, A Coluccio, M Frejno, ... Nature methods 19 (7), 803-811, 2022 | 33 | 2022 |
Universal spectrum explorer: a standalone (web-) application for cross-resource spectrum comparison T Schmidt, P Samaras, V Dorfer, C Panse, T Kockmann, L Bichmann, ... Journal of proteome research 20 (6), 3388-3394, 2021 | 32 | 2021 |
Proteomic and transcriptomic profiling of aerial organ development in Arabidopsis J Mergner, M Frejno, M Messerer, D Lang, P Samaras, M Wilhelm, ... Scientific Data 7 (1), 334, 2020 | 27 | 2020 |
FIFS: A data mining method for informative marker selection in high dimensional population genomic data I Kavakiotis, P Samaras, A Triantafyllidis, I Vlahavas Computers in biology and medicine 90, 146-154, 2017 | 22 | 2017 |
A prediction model of passenger demand using AVL and APC data from a bus fleet P Samaras, A Fachantidis, G Tsoumakas, I Vlahavas Proceedings of the 19th panhellenic conference on informatics, 129-134, 2015 | 22 | 2015 |
Chemical proteomics reveals the target landscape of 1,000 kinase inhibitors M Reinecke, P Brear, L Vornholz, BT Berger, F Seefried, S Wilhelm, ... Nature Chemical Biology 20 (5), 577-585, 2024 | 20 | 2024 |
Reanalysis of ProteomicsDB using an accurate, sensitive, and scalable false discovery rate estimation approach for protein groups P Samaras, B Kuster, M Wilhelm Molecular & Cellular Proteomics 21 (12), 2022 | 13 | 2022 |