Wilhelm, Mathias

Mass-spectrometry-based draft of the human proteome

Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A. M., Lieberenz, M., Savitski, M. M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H., et al. (2014) · Nature

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 1,820

The target landscape of clinical kinase drugs

Klaeger, S., Heinzlmeir, S., Wilhelm, M., Polzer, H., Vick, B., Koenig, P.-A., Reinecke, M., Ruprecht, B., Petzoldt, S., Meng, C., et al. (2017) · Science

Computational Drug Discovery MethodsAdvanced Proteomics Techniques and Applications

Cited by 854

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Wang, D., Eraslan, B., Wieland, T., Hallström, B., Hopf, T., Zolg, D. P., Zecha, J., Asplund, A., Li, L., Meng, C., et al. (2019) · Molecular Systems Biology

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 750

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Wang, D., Eraslan, B., Wieland, T., Hallström, B., Hopf, T., Zolg, D. P., Zecha, J., Asplund, A., Li, L.-H., Meng, C., et al. (2018) · Molecular Systems Biology

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 750

Global Proteome Analysis of the NCI-60 Cell Line Panel

Gholami, A. M., Hahne, H., Wu, Z., Auer, F. J., Meng, C., Wilhelm, M., & Kuster, B. (2013) · Cell Reports

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 302

Chemical Proteomics and Structural Biology Define EPHA2 Inhibition by Clinical Kinase Drugs

Heinzlmeir, S., Kudlinzki, D., Sreeramulu, S., Klaeger, S., Gande, S. L., Linhard, V., Wilhelm, M., Qiao, H., Helm, D., Ruprecht, B., et al. (2016) · ACS Chemical Biology

Computational Drug Discovery MethodsProtein Kinase Regulation and GTPase Signaling

Cited by 56

PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New Proteoforms

Verbruggen, S., Ndah, E., Van Criekinge, W., Gessulat, S., Kuster, B., Wilhelm, M., Van Damme, P., & Menschaert, G. (2019) · Molecular & Cellular Proteomics

Advanced Proteomics Techniques and ApplicationsRNA and protein synthesis mechanisms

Cited by 45

Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins

Hao, Y., Colak, R., Teyra, J., Corbi-Verge, C., Ignatchenko, A., Hahne, H., Wilhelm, M., Kuster, B., Braun, P., Kaida, D., et al. (2015) · Cell Reports

RNA Research and SplicingGenomics and Phylogenetic Studies

Cited by 23

To Fly, or Not to Fly, That Is the Question: A Deep Learning Model for Peptide Detectability Prediction in Mass Spectrometry

Abdul-Khalek, N., Picciani, M., Shouman, O., Wimmer, R., Overgaard, M. T., Wilhelm, M., & Gregersen Echers, S. (2025) · Journal of Proteome Research

Advanced Proteomics Techniques and ApplicationsMachine Learning in Bioinformatics

Cited by 13

Pairwise Attention: Leveraging Mass Differences to Enhance De Novo Sequencing of Mass Spectra

Lapin, J., Nilsson, A., Wilhelm, M., & Käll, L. (2025) · Journal of Proteome Research

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 4

Pairwise Attention: Leveraging Mass Differences to Enhance De Novo Sequencing of Mass Spectra

Lapin, J., Nilsson, A., Wilhelm, M., & Käll, L. (2025) · Journal of Proteome Research

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 4

Modanovo: A Unified Model for Post-Translational Modification-Aware de Novo Sequencing Using Experimental Spectra from In Vivo and Synthetic Peptides

Klaproth-Andrade, D., Bruns, Y., Gabriel, W., Nix, C., Bergant, V., Pichlmair, A., Wilhelm, M., & Gagneur, J. (2025) · Molecular & Cellular Proteomics

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 4