| A global screen for assembly state changes of the mitotic proteome by SEC-SWATH-MS M Heusel, M Frank, M Köhler, S Amon, F Frommelt, G Rosenberger, ... Cell systems 10 (2), 133-155. e6, 2020 | 65 | 2020 |
| A practical guide to interpreting and generating bottom‐up proteomics data visualizations JP Schessner, E Voytik, I Bludau Proteomics 22 (8), 2100103, 2022 | 21 | 2022 |
| ACEseq–allele specific copy number estimation from whole genome sequencing K Kleinheinz, I Bludau, D Hübschmann, M Heinold, P Kensche, Z Gu, ... BioRXiv, 210807, 2017 | 35 | 2017 |
| ACEseq—allele specific copy number estimation from whole genome sequencing. bioRxiv 210807 K Kleinheinz, I Bludau, D Huebschmann | 6 | 2017 |
| AlphaMap: an open-source Python package for the visual annotation of proteomics data with sequence-specific knowledge E Voytik, I Bludau, S Willems, FM Hansen, AD Brunner, MT Strauss, ... Bioinformatics 38 (3), 849-852, 2022 | 14 | 2022 |
| AlphaPept: a modern and open framework for MS-based proteomics MT Strauss, I Bludau, WF Zeng, E Voytik, C Ammar, JP Schessner, ... Nature Communications 15 (1), 2168, 2024 | 31 | 2024 |
| AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics WF Zeng, XX Zhou, S Willems, C Ammar, M Wahle, I Bludau, E Voytik, ... Nature Communications 13 (1), 7238, 2022 | 75 | 2022 |
| AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics E Krismer, I Bludau, MT Strauss, M Mann Bioinformatics 39 (8), btad461, 2023 | 5 | 2023 |
| Complex-centric proteome profiling I Bludau, R Aebersold | | |
| Complex-centric proteome profiling by SEC-SWATH-MS I Bludau, M Heusel, G Rosenberger, R Hafen, M Frank, ... MOLECULAR & CELLULAR PROTEOMICS 18 (8), S15-S15, 2019 | 1 | 2019 |
| Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes I Bludau, M Heusel, M Frank, G Rosenberger, R Hafen, ... Nature protocols, 1-47, 2020 | 44 | 2020 |
| Complex‐centric proteome profiling by SEC‐SWATH‐MS M Heusel, I Bludau, G Rosenberger, R Hafen, M Frank, ... Molecular systems biology 15 (1), e8438, 2019 | 140 | 2019 |
| Data-independent acquisition method for ubiquitinome analysis reveals regulation of circadian biology FM Hansen, MC Tanzer, F Brüning, I Bludau, C Stafford, BA Schulman, ... Nature Communications 12 (1), 254, 2021 | 90 | 2021 |
| Degroe e, S.,… Palmblad, M.(2023) B Neel, V Dorfer, L Martens, I Bludau, R Bouwmeester Toward an integrated machine Learning model of a proteomics experiment.(3 …, 0 | | |
| diaPASEF: parallel accumulation–serial fragmentation combined with data-independent acquisition F Meier, AD Brunner, M Frank, A Ha, I Bludau, E Voytik, ... Nature methods 17 (12), 1229-1236, 2020 | 466 | 2020 |
| Discovery–versus hypothesis–driven detection of protein–protein interactions and complexes I Bludau International Journal of Molecular Sciences 22 (9), 4450, 2021 | 12 | 2021 |
| Genomic, proteomic and phenotypic heterogeneity in HeLa cells across laboratories: implications for reproducibility of research results Y Liu, Y Mi, T Mueller, S Kreibich, EG Williams, A Van Drogen, C Borel, ... bioRxiv, 307421, 2018 | 10 | 2018 |
| Integration of transcriptome, proteome and phosphoproteome data elucidates the genetic control of molecular networks J Großbach, L Gillet, M Clément-Ziza, CL Schmalohr, OT Schubert, ... bioRxiv, 703140, 2019 | 8 | 2019 |
| Integrative proteomics reveals principles of dynamic phosphosignaling networks in human erythropoiesis Ö Karayel, P Xu, I Bludau, S Velan Bhoopalan, Y Yao, FC Ana Rita, ... Molecular systems biology 16 (12), e9813, 2020 | 28 | 2020 |
| Mitochondrial phosphoproteomes are functionally specialized across tissues FM Hansen, LS Kremer, O Karayel, I Bludau, NG Larsson, I Kühl, M Mann Life Science Alliance 7 (2), 2024 | 13 | 2024 |
