Moritz Heusel

1.6k total citations
17 papers, 715 citations indexed

About

Moritz Heusel is a scholar working on Molecular Biology, Spectroscopy and Materials Chemistry. According to data from OpenAlex, Moritz Heusel has authored 17 papers receiving a total of 715 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 13 papers in Spectroscopy and 3 papers in Materials Chemistry. Recurrent topics in Moritz Heusel's work include Advanced Proteomics Techniques and Applications (13 papers), Mass Spectrometry Techniques and Applications (7 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Moritz Heusel is often cited by papers focused on Advanced Proteomics Techniques and Applications (13 papers), Mass Spectrometry Techniques and Applications (7 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Moritz Heusel collaborates with scholars based in Switzerland, United States and Sweden. Moritz Heusel's co-authors include Ruedi Aebersold, Isabell Bludau, Ben C. Collins, George Rosenberger, Max Frank, Matthias Gstaiger, Yansheng Liu, Amir Banaei‐Esfahani, Audrey van Drogen and Hannes Röst and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and The EMBO Journal.

In The Last Decade

Moritz Heusel

17 papers receiving 711 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Moritz Heusel Switzerland 13 566 354 106 53 49 17 715
Martin Soste Switzerland 14 803 1.4× 414 1.2× 108 1.0× 72 1.4× 28 0.6× 19 1.1k
Max Frank Switzerland 9 588 1.0× 410 1.2× 96 0.9× 13 0.2× 27 0.6× 13 833
Erik L. de Graaf Netherlands 15 573 1.0× 390 1.1× 33 0.3× 22 0.4× 15 0.3× 24 785
Shubin Ren Germany 4 600 1.1× 292 0.8× 75 0.7× 18 0.3× 8 0.2× 4 680
Julian Vasilescu Canada 11 466 0.8× 200 0.6× 84 0.8× 17 0.3× 14 0.3× 14 642
Paul T. Jedrzejewski United States 11 427 0.8× 364 1.0× 60 0.6× 18 0.3× 12 0.2× 16 723
Christian M. Beusch Sweden 10 355 0.6× 139 0.4× 44 0.4× 15 0.3× 15 0.3× 20 495
Naoto Soya Canada 13 524 0.9× 79 0.2× 90 0.8× 47 0.9× 289 5.9× 15 928
A. Saskia Venne Germany 10 502 0.9× 207 0.6× 48 0.5× 14 0.3× 16 0.3× 11 684
Christian Marsching Germany 16 462 0.8× 243 0.7× 66 0.6× 11 0.2× 20 0.4× 20 650

Countries citing papers authored by Moritz Heusel

Since Specialization
Citations

This map shows the geographic impact of Moritz Heusel'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 Moritz Heusel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moritz Heusel more than expected).

Fields of papers citing papers by Moritz Heusel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Moritz Heusel. 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 Moritz Heusel. The network helps show where Moritz Heusel may publish in the future.

Co-authorship network of co-authors of Moritz Heusel

This figure shows the co-authorship network connecting the top 25 collaborators of Moritz Heusel. A scholar is included among the top collaborators of Moritz Heusel 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 Moritz Heusel. Moritz Heusel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Toledo, Alejandro Gómez, et al.. (2025). Epitope Mapping with Sidewinder: An XL-MS and Structural Modeling Approach. International Journal of Molecular Sciences. 26(4). 1488–1488. 1 indexed citations
2.
Frommelt, Fabian, Andrea Fossati, Federico Uliana, et al.. (2024). DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes. Nature Methods. 21(4). 635–647. 11 indexed citations
3.
Tanner, Lloyd, Andrew Single, Ravi K. V. Bhongir, et al.. (2023). Small-molecule-mediated OGG1 inhibition attenuates pulmonary inflammation and lung fibrosis in a murine lung fibrosis model. Nature Communications. 14(1). 643–643. 52 indexed citations
4.
Happonen, Lotta, et al.. (2023). Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics. PLoS Computational Biology. 19(1). e1010457–e1010457. 4 indexed citations
5.
Bludau, Isabell, Claudia Martelli, Peng Xue, et al.. (2023). Rapid Profiling of Protein Complex Reorganization in Perturbed Systems. Journal of Proteome Research. 22(5). 1520–1536. 14 indexed citations
6.
Karlsson, Christofer, et al.. (2022). MSLibrarian: Optimized Predicted Spectral Libraries for Data-Independent Acquisition Proteomics. Journal of Proteome Research. 21(2). 535–546. 10 indexed citations
7.
Fossati, Andrea, Chen Li, Federico Uliana, et al.. (2021). PCprophet: a framework for protein complex prediction and differential analysis using proteomic data. Nature Methods. 18(5). 520–527. 43 indexed citations
8.
Bludau, Isabell, Max Frank, Christian Dörig, et al.. (2021). Systematic detection of functional proteoform groups from bottom-up proteomic datasets. Nature Communications. 12(1). 3810–3810. 45 indexed citations
9.
Bludau, Isabell, Moritz Heusel, Max Frank, et al.. (2020). Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes. Nature Protocols. 15(8). 2341–2386. 44 indexed citations
10.
Rosenberger, George, Moritz Heusel, Isabell Bludau, et al.. (2020). SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles. Cell Systems. 11(6). 589–607.e8. 29 indexed citations
11.
Heusel, Moritz, Max Frank, Sabine Amon, et al.. (2020). A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS. Cell Systems. 10(2). 133–155.e6. 51 indexed citations
12.
Heusel, Moritz, Isabell Bludau, George Rosenberger, et al.. (2019). Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS. Molecular Systems Biology. 15(1). e8438–e8438. 92 indexed citations
13.
Heusel, Moritz, Julien Duc, Cécile Piot, et al.. (2019). The interactome of KRAB zinc finger proteins reveals the evolutionary history of their functional diversification. The EMBO Journal. 38(18). e101220–e101220. 64 indexed citations
14.
Caron, Étienne, Romain Roncagalli, Takeshi Hase, et al.. (2017). Precise Temporal Profiling of Signaling Complexes in Primary Cells Using SWATH Mass Spectrometry. Cell Reports. 18(13). 3219–3226. 27 indexed citations
15.
Rosenberger, George, Isabell Bludau, Uwe Schmitt, et al.. (2017). Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nature Methods. 14(9). 921–927. 144 indexed citations
16.
Blattmann, Peter, Moritz Heusel, & Ruedi Aebersold. (2016). SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools. PLoS ONE. 11(4). e0153160–e0153160. 33 indexed citations
17.
McMillin, Sara M., Moritz Heusel, Tong Liu, Stefano Costanzi, & Jürgen Wess. (2011). Structural Basis of M3 Muscarinic Receptor Dimer/Oligomer Formation. Journal of Biological Chemistry. 286(32). 28584–28598. 51 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.

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