| Prosit-TMT: deep learning boosts identification of TMT-labeled peptides W Gabriel, M The, DP Zolg, FP Bayer, O Shouman, L Lautenbacher, ... Analytical Chemistry 94 (20), 7181-7190, 2022 | 11 | 2022 |
| Oktoberfest: Open‐source spectral library generation and rescoring pipeline based on Prosit M Picciani, W Gabriel, VG Giurcoiu, O Shouman, F Hamood, ... Proteomics, 2300112, 2023 | 7 | 2023 |
| PROSPECT: Labeled tandem mass spectrometry dataset for machine learning in proteomics O Shouman, W Gabriel, VG Giurcoiu, V Sternlicht, M Wilhelm Advances in Neural Information Processing Systems 35, 32882-32896, 2022 | 6 | 2022 |
| Experiences from teaching practical machine learning courses to master’s students with mixed backgrounds O Shouman, S Fuchs, H Wittges The Second Teaching Machine Learning and Artificial Intelligence Workshop, 62-67, 2022 | 6 | 2022 |
| An Overview of Explainable Predictive Process Monitoring C Drieschner, S Ibishi, O Shouman, H Wittges, H Krcmar SAP Academic Community Conference 2021 DACH, 2021 | 1 | 2021 |
| Prosit boosts mass spectrometry-based proteomics one spectrum at a time M Wilhelm, W Gabriel, O Shouman, V Sternlicht, L Lautenbacher MOLECULAR & CELLULAR PROTEOMICS 21 (8), S23-S23, 2022 | | 2022 |
Mathias WilhelmComputational Mass Spectrometry, Technical University of MunichBestätigte E-Mail-Adresse bei tum.de
