Matthias Gstaiger

10.3k total citations · 1 hit paper
72 papers, 6.4k citations indexed

About

Matthias Gstaiger is a scholar working on Molecular Biology, Spectroscopy and Cell Biology. According to data from OpenAlex, Matthias Gstaiger has authored 72 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 21 papers in Spectroscopy and 14 papers in Cell Biology. Recurrent topics in Matthias Gstaiger's work include Advanced Proteomics Techniques and Applications (20 papers), Ubiquitin and proteasome pathways (12 papers) and Bioinformatics and Genomic Networks (11 papers). Matthias Gstaiger is often cited by papers focused on Advanced Proteomics Techniques and Applications (20 papers), Ubiquitin and proteasome pathways (12 papers) and Bioinformatics and Genomic Networks (11 papers). Matthias Gstaiger collaborates with scholars based in Switzerland, United States and Germany. Matthias Gstaiger's co-authors include Ruedi Aebersold, Timo Glatter, Wilhelm Krek, Alexander Wepf, Anne‐Claude Gingras, Brian Raught, Oleg Georgiev, Audrey van Drogen, Markku Varjosalo and Walter Schaffner and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Matthias Gstaiger

72 papers receiving 6.3k 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.

Analysis of protein complexes using mass spectrometry

2007 539 citations Anne‐Claude Gingras, Matthias Gstaiger et al. Nature Reviews Molecular Cell Biology profile →

Peers

Countries citing papers authored by Matthias Gstaiger

Since Specialization

Citations

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

Fields of papers citing papers by Matthias Gstaiger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Gstaiger

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Discovery of an exquisitely selective WDR5 chemical probe accelerated by a high-quality DEL–ML Hit 2025 ·RSC Chemical Biology ·(unknown), (unknown), (unknown), Serah Kimani, (unknown), (unknown), Martin P. Schwalm, H. Holzmann, Andreas Krämer, A. Dong, Fengling Li, Irene Chau, (unknown), Matthias Gstaiger, Susanne Müller, Stefan Knapp, Václav Němec	1
2	A tissue-specific atlas of protein–protein associations enables prioritization of candidate disease genes 2025 ·Nature Biotechnology ·(unknown), Marc van Oostrum, Danish Memon, Fabian Frommelt, Delora Baptista, Kalpana Panneerselvam, Glyn Bradley, Luana Licata, Henning Hermjakob, Sandra Orchard, Gosia Trynka, Ellen M. McDonagh, Andrea Fossati, Ruedi Aebersold, Matthias Gstaiger, Bernd Wollscheid, Pedro Beltrão	4
3	DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes 2024 ·Nature Methods ·Fabian Frommelt, Andrea Fossati, Federico Uliana, Fabian Wendt, Peng Xue, Moritz Heusel, Bernd Wollscheid, Ruedi Aebersold, Rodolfo Ciuffa, Matthias Gstaiger	11
4	Rapid, potent, and persistent covalent chemical probes to deconvolute PI3Kα signaling 2024 ·Chemical Science ·(unknown), (unknown), Erhan Keleş, Luka Raguž, (unknown), (unknown), Thorsten Schaefer, (unknown), Thomas Bohnacker, Rohitha Sriramaratnam, Alexander Schäfer, Matthias Gstaiger, John E. Burke, Chiara Borsari, Matthias P. Wymann	1
5	Harnessing CD3 diversity to optimize CAR T cells 2023 ·Nature Immunology ·Rubí M.-H. Velasco Cárdenas, Simon M. Brandl, (unknown), Alexandra Emilia Schlaak, (unknown), Timo Peters, Fabian Beier, Bryan Serrels, Sanaz Taromi, (unknown), Simon Hauri, Matthias Gstaiger, Silke Laßmann, Johannes B. Huppa, Melanie Boerries, Geoffroy Andrieux, Bertram Bengsch, Wolfgang W. Schamel, Susana Minguet	42
6	Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics 2022 ·Proceedings of the National Academy of Sciences ·Rodolfo Ciuffa, Federico Uliana, (unknown), Martin Mehnert, Tencho Tenev, (unknown), (unknown), (unknown), (unknown), Alessandro Ori‬‬, Matthias Gstaiger, Pascal Meier, Ruedi Aebersold	10
7	Covalent Proximity Scanning of a Distal Cysteine to Target PI3Kα 2022 ·Journal of the American Chemical Society ·Chiara Borsari, Erhan Keleş, Jacob A. McPhail, (unknown), Rohitha Sriramaratnam, (unknown), Thorsten Schaefer, (unknown), Wojciech Bal, Matthias Gstaiger, John E. Burke, Matthias P. Wymann	40
8	PCprophet: a framework for protein complex prediction and differential analysis using proteomic data 2021 ·Nature Methods ·Andrea Fossati, Chen Li, Federico Uliana, Fabian Wendt, Fabian Frommelt, Peter Sykacek, Moritz Heusel, (unknown), Isabell Bludau, (unknown), Peng Xue, Jiangning Song, Bernd Wollscheid, Anthony W. Purcell, Matthias Gstaiger, Ruedi Aebersold	43
9	Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes 2020 ·Nature Protocols ·Isabell Bludau, Moritz Heusel, Max Frank, George Rosenberger, (unknown), Amir Banaei‐Esfahani, Audrey van Drogen, Ben C. Collins, Matthias Gstaiger, Ruedi Aebersold	44
10	Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes 2020 ·Nature Communications ·Martin Mehnert, Rodolfo Ciuffa, Fabian Frommelt, Federico Uliana, Audrey van Drogen, (unknown), Matthias Gstaiger, Ruedi Aebersold	24
11	Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS 2019 ·Molecular Systems Biology ·Moritz Heusel, Isabell Bludau, George Rosenberger, (unknown), Max Frank, Amir Banaei‐Esfahani, Audrey van Drogen, Ben C. Collins, Matthias Gstaiger, Ruedi Aebersold	92
12	The Leukemogenic TCF3-HLF Complex Rewires Enhancers Driving Cellular Identity and Self-Renewal Conferring EP300 Vulnerability 2019 ·Cancer Cell ·Yun Huang, (unknown), Hans-Jörg Warnatz, Thomas S. Risch, (unknown), Fabian Frommelt, Quy A. Ngo, Maria Pamela Dobay, Blerim Marovca, Silvia Jenni, Yi-Chien Tsai, Sören Matzk, Vyacheslav Amstislavskiy, Martin Schrappe, Martin Stanulla, Matthias Gstaiger, Beat Bornhäuser, Marie‐Laure Yaspo, Jean‐Pierre Bourquin	32
13	The unconventional myosin CRINKLED and its mammalian orthologue MYO7A regulate caspases in their signalling roles 2016 ·Nature Communications ·Mariam Orme, Gianmaria Liccardi, (unknown), Rebecca Feltham, (unknown), Tencho Tenev, Lior Aram, Rebecca Wilson, Katiuscia Bianchi, Otto Morris, (unknown), David Robertson, Meghana Tare, Alexander Wepf, David S. Williams, Andreas Bergmann, Matthias Gstaiger, Eli Arama, Paulo S. Ribeiro, Pascal Meier	26
14	Genotype–phenotype relationships in light of a modular protein interaction landscape 2013 ·Molecular BioSystems ·Matthias Gstaiger, Ruedi Aebersold	5
15	The Protein Interaction Landscape of the Human CMGC Kinase Group 2013 ·Cell Reports ·Markku Varjosalo, Salla Keskitalo, Audrey van Drogen, (unknown), Anton Vichalkovski, Ruedi Aebersold, Matthias Gstaiger	159
16	Tandem affinity purification combined with inducible shRNA expression as a tool to study the maturation of macromolecular assemblies 2010 ·RNA ·Emanuel Wyler, (unknown), (unknown), Matthias Gstaiger, Jens Pfannstiel, Ulrike Kutay, Ivo Zemp	38
17	Applying mass spectrometry-based proteomics to genetics, genomics and network biology 2009 ·Nature Reviews Genetics ·Matthias Gstaiger, Ruedi Aebersold	330
18	Analysis of protein complexes using mass spectrometry breakdown → 2007 ·Nature Reviews Molecular Cell Biology ·Anne‐Claude Gingras, Matthias Gstaiger, Brian Raught, Ruedi Aebersold	539
19	S6K1-Mediated Disassembly of Mitochondrial URI/PP1γ Complexes Activates a Negative Feedback Program that Counters S6K1 Survival Signaling 2007 ·Molecular Cell ·Nabil Djouder, (unknown), Alexander Schmidt, C Wirbelauer, Matthias Gstaiger, Ruedi Aebersold, Daniel Heß, Wilhelm Krek	91
20	The HRPT2 Tumor Suppressor Gene Product Parafibromin Associates with Human PAF1 and RNA Polymerase II 2005 ·Molecular and Cellular Biology ·Armelle Yart, Matthias Gstaiger, C Wirbelauer, (unknown), Dimitrios Anastasiou, Daniel Heß, Wilhelm Krek	155

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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