Mathias Wilhelm

11.4k total citations · 2 hit papers
93 papers, 3.7k citations indexed

About

Mathias Wilhelm is a scholar working on Molecular Biology, Spectroscopy and Oncology. According to data from OpenAlex, Mathias Wilhelm has authored 93 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 48 papers in Spectroscopy and 13 papers in Oncology. Recurrent topics in Mathias Wilhelm's work include Advanced Proteomics Techniques and Applications (46 papers), Mass Spectrometry Techniques and Applications (22 papers) and Metabolomics and Mass Spectrometry Studies (18 papers). Mathias Wilhelm is often cited by papers focused on Advanced Proteomics Techniques and Applications (46 papers), Mass Spectrometry Techniques and Applications (22 papers) and Metabolomics and Mass Spectrometry Studies (18 papers). Mathias Wilhelm collaborates with scholars based in Germany, United States and United Kingdom. Mathias Wilhelm's co-authors include Bernhard Küster, Hannes Hahne, Tobias Schmidt, Daniel P. Zolg, Siegfried Gessulat, Patroklos Samaras, Karsten Schnatbaum, Chen Meng, Marcus Bantscheff and Mikhail M. Savitski and has published in prestigious journals such as Nature, Nucleic Acids Research and Nature Communications.

In The Last Decade

Mathias Wilhelm

88 papers receiving 3.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning

2019 519 citations Siegfried Gessulat, Tobias Schmidt et al. profile →
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

2019 449 citations Daniel P. Zolg, Tobias Schmidt et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mathias Wilhelm Germany	29	2.5k	1.4k	452	248	229	93	3.7k
Pedro Navarro Spain	17	3.0k 1.2×	2.2k 1.5×	204 0.5×	258 1.0×	227 1.0×	26	4.3k
Yunping Zhu China	28	2.5k 1.0×	712 0.5×	451 1.0×	402 1.6×	464 2.0×	112	4.1k
Sander R. Piersma Netherlands	40	2.8k 1.1×	1.1k 0.8×	687 1.5×	270 1.1×	852 3.7×	137	4.7k
Pavel Gromov Denmark	32	1.9k 0.8×	753 0.5×	566 1.3×	378 1.5×	537 2.3×	78	2.9k
Zhi Sun United States	24	3.0k 1.2×	1.8k 1.3×	271 0.6×	230 0.9×	226 1.0×	52	4.1k
An Staes Belgium	34	2.6k 1.0×	1.3k 0.9×	758 1.7×	272 1.1×	366 1.6×	78	3.9k
William M. Old United States	30	2.9k 1.1×	1.4k 1.0×	306 0.7×	175 0.7×	170 0.7×	56	3.8k
Ben C. Collins Switzerland	28	3.0k 1.2×	2.2k 1.5×	247 0.5×	223 0.9×	235 1.0×	54	4.3k
Thang V. Pham Netherlands	35	2.2k 0.9×	694 0.5×	599 1.3×	241 1.0×	764 3.3×	134	3.4k
Ludovic Gillet Switzerland	28	4.7k 1.9×	3.0k 2.1×	395 0.9×	271 1.1×	471 2.1×	39	6.3k

Countries citing papers authored by Mathias Wilhelm

Since Specialization

Citations

This map shows the geographic impact of Mathias Wilhelm's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mathias Wilhelm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathias Wilhelm more than expected).

Fields of papers citing papers by Mathias Wilhelm

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mathias Wilhelm. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mathias Wilhelm. The network helps show where Mathias Wilhelm may publish in the future.

Co-authorship network of co-authors of Mathias Wilhelm

This figure shows the co-authorship network connecting the top 25 collaborators of Mathias Wilhelm. A scholar is included among the top collaborators of Mathias Wilhelm based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mathias Wilhelm. Mathias Wilhelm is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wilhelm, Mathias, et al.. (2026). High-throughput chemical proteomics workflow for profiling protein citrullination dynamics. Nature Communications. 17(1).

Müller, Julian, et al.. (2025). PTMNavigator: interactive visualization of differentially regulated post-translational modifications in cellular signaling pathways. Nature Communications. 16(1). 510–510. 6 indexed citations

Poppenberger, Brigitte, et al.. (2025). Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes. Molecular & Cellular Proteomics. 24(3). 100924–100924. 3 indexed citations

Fischer, Lutz, et al.. (2025). Prosit-XL: enhanced cross-linked peptide identification by fragment intensity prediction to study protein interactions and structures. mediaTUM (Technical University of Munich). 16(1). 5429–5429. 2 indexed citations

Zhang, Ning, Li Tang, Songgang Li, et al.. (2025). Integration of multi-omics data accelerates molecular analysis of common wheat traits. Nature Communications. 16(1). 2200–2200. 9 indexed citations

Wilhelm, Mathias, et al.. (2024). Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification. Molecular & Cellular Proteomics. 23(7). 100798–100798. 12 indexed citations

Jeffery, Erin D., et al.. (2024). IS-PRM-Based Peptide Targeting Informed by Long-Read Sequencing for Alternative Proteome Detection. Journal of the American Society for Mass Spectrometry. 35(11). 2614–2630. 3 indexed citations

Smith, Nicholas H., et al.. (2024). Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing. Nature Communications. 15(1). 151–151. 15 indexed citations

Wilhelm, Mathias, et al.. (2024). Exploring crop genomes: assembly features, gene prediction accuracy, and implications for proteomics studies. BMC Genomics. 25(1). 619–619. 7 indexed citations

10.

Reinecke, Maria, P. Brear, Larsen Vornholz, et al.. (2023). Chemical proteomics reveals the target landscape of 1,000 kinase inhibitors. Nature Chemical Biology. 20(5). 577–585. 35 indexed citations

11.

Neely, Benjamin A., Viktoria Dorfer, Lennart Martens, et al.. (2023). Toward an Integrated Machine Learning Model of a Proteomics Experiment. Journal of Proteome Research. 22(3). 681–696. 35 indexed citations

12.

Bian, Yangyang, Matthew The, Piero Giansanti, et al.. (2021). Identification of 7 000–9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC–MS/MS. Analytical Chemistry. 93(25). 8687–8692. 29 indexed citations

13.

Schmidt, Tobias, Patroklos Samaras, Viktoria Dorfer, et al.. (2021). Universal Spectrum Explorer: A Standalone (Web-)Application for Cross-Resource Spectrum Comparison. Journal of Proteome Research. 20(6). 3388–3394. 21 indexed citations

14.

Verbruggen, Steven, Siegfried Gessulat, Ralf Gabriels, et al.. (2021). Spectral Prediction Features as a Solution for the Search Space Size Problem in Proteogenomics. Molecular & Cellular Proteomics. 20. 100076–100076. 26 indexed citations

15.

Searle, Brian C., Kristian E. Swearingen, Christopher A. Barnes, et al.. (2020). Generating high quality libraries for DIA MS with empirically corrected peptide predictions. Nature Communications. 11(1). 1548–1548. 166 indexed citations

16.

Reinecke, Maria, Benjamin Ruprecht, Svenja Wiechmann, et al.. (2019). Chemoproteomic Selectivity Profiling of PIKK and PI3K Kinase Inhibitors. ACS Chemical Biology. 14(4). 655–664. 23 indexed citations

17.

Schmidt, Tobias, et al.. (2019). CiRCus: A Framework to Enable Classification of Complex High-Throughput Experiments. Journal of Proteome Research. 18(4). 1486–1493. 2 indexed citations

18.

Yu, Peng, Svenja Wiechmann, Mathias Wilhelm, et al.. (2017). Trimodal Mixed Mode Chromatography That Enables Efficient Offline Two-Dimensional Peptide Fractionation for Proteome Analysis. Analytical Chemistry. 89(17). 8884–8891. 17 indexed citations

19.

Sasse, Stephanie, Beate Klimm, Helen Görgen, et al.. (2012). Comparing long-term toxicity and efficacy of combined modality treatment including extended- or involved-field radiotherapy in early-stage Hodgkin's lymphoma. Annals of Oncology. 23(11). 2953–2959. 25 indexed citations

20.

Wendtner, C.‐M., Barbara Schmitt, Mathias Wilhelm, et al.. (1999). Redefining the therapeutic goals in chronic lymphocytic leukemia: Towards an evidence-based, risk-adapted therapy. Annals of Oncology. 10(5). 505–510. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact