Kalle Gehring

12.3k total citations · 2 hit papers
198 papers, 9.3k citations indexed

About

Kalle Gehring is a scholar working on Molecular Biology, Cell Biology and Materials Chemistry. According to data from OpenAlex, Kalle Gehring has authored 198 papers receiving a total of 9.3k indexed citations (citations by other indexed papers that have themselves been cited), including 149 papers in Molecular Biology, 44 papers in Cell Biology and 25 papers in Materials Chemistry. Recurrent topics in Kalle Gehring's work include RNA and protein synthesis mechanisms (36 papers), Ubiquitin and proteasome pathways (30 papers) and Enzyme Structure and Function (25 papers). Kalle Gehring is often cited by papers focused on RNA and protein synthesis mechanisms (36 papers), Ubiquitin and proteasome pathways (30 papers) and Enzyme Structure and Function (25 papers). Kalle Gehring collaborates with scholars based in Canada, United States and France. Kalle Gehring's co-authors include Guennadi Kozlov, M. Guéron, Jean‐Louis Leroy, David Y. Thomas, Pekka Määttänen, Jean‐François Trempe, Irena Ekiel, Tudor Moldoveanu, Véronique Sauvé and Hiroshi Nikaido and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Kalle Gehring

195 papers receiving 9.2k citations

Hit Papers

A tetrameric DNA structure with protonated cytosine-cytos... 1993 2026 2004 2015 1993 2013 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kalle Gehring Canada 53 7.0k 1.8k 1.2k 869 775 198 9.3k
Toshiaki Isobe Japan 62 10.1k 1.4× 1.6k 0.9× 1.3k 1.1× 1.0k 1.2× 1.5k 2.0× 247 13.4k
Gerard Manning United States 38 9.6k 1.4× 2.2k 1.3× 584 0.5× 692 0.8× 1.0k 1.3× 52 12.9k
Douglas Cyr United States 47 7.0k 1.0× 2.8k 1.6× 917 0.8× 476 0.5× 834 1.1× 113 9.2k
Mathew E. Sowa United States 40 9.7k 1.4× 2.4k 1.3× 2.3k 1.9× 460 0.5× 707 0.9× 50 12.0k
Toshiya Endo Japan 57 8.6k 1.2× 1.8k 1.0× 1.3k 1.1× 376 0.4× 437 0.6× 184 9.8k
Gergely L. Lukács Canada 61 6.6k 0.9× 2.1k 1.2× 941 0.8× 611 0.7× 819 1.1× 198 12.3k
Robert Schwarzenbacher United States 33 4.8k 0.7× 641 0.4× 735 0.6× 759 0.9× 989 1.3× 51 6.7k
Andreas Bracher Germany 47 8.2k 1.2× 2.3k 1.3× 626 0.5× 505 0.6× 688 0.9× 100 10.1k
Mikako Shirouzu Japan 63 11.2k 1.6× 1.6k 0.9× 909 0.7× 755 0.9× 1.0k 1.3× 390 14.7k
Elizabeth J. Goldsmith United States 50 9.8k 1.4× 1.5k 0.9× 355 0.3× 570 0.7× 834 1.1× 108 12.7k

Countries citing papers authored by Kalle Gehring

Since Specialization
Citations

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

Fields of papers citing papers by Kalle Gehring

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kalle Gehring

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

All Works

20 of 20 papers shown
1.
Kozlov, Guennadi, et al.. (2025). Deep Mutational Scanning of an Engineered High-affinity Ligand of the poly(A) Binding Protein MLLE Domain. Journal of Molecular Biology. 437(12). 169120–169120.
2.
Zong, Pengyu, Jianlin Feng, Huanquan Zheng, et al.. (2025). The cytoplasmic domains of the CNNM family of transmembrane proteins modulate the ion channel-kinase TRPM7. Journal of Biological Chemistry. 301(11). 110720–110720.
3.
Sauvé, Véronique, et al.. (2024). Structural basis for the pathogenicity of parkin catalytic domain mutants. Journal of Biological Chemistry. 301(1). 108051–108051. 4 indexed citations
4.
Huq, Tahrima Saiha, et al.. (2024). Naturally occurring hyperactive variants of human parkin. Communications Biology. 7(1). 961–961. 1 indexed citations
5.
Sauvé, Véronique, Eric Stefan, Nathalie Croteau, et al.. (2024). Activation of parkin by a molecular glue. Nature Communications. 15(1). 7707–7707. 17 indexed citations
6.
Sauvé, Véronique & Kalle Gehring. (2024). A molecular glue for PRKN/parkin. Autophagy. 21(3). 689–690. 1 indexed citations
7.
Song, Pingping, Wesley Peng, Véronique Sauvé, et al.. (2023). Parkinson’s disease-linked parkin mutation disrupts recycling of synaptic vesicles in human dopaminergic neurons. Neuron. 111(23). 3775–3788.e7. 29 indexed citations
8.
Gehring, Kalle, et al.. (2023). New insights into the structure and function of CNNM proteins. FEBS Journal. 290(23). 5475–5495. 7 indexed citations
9.
Kozlov, Guennadi, et al.. (2023). Structural insights into regulation of CNNM-TRPM7 divalent cation uptake by the small GTPase ARL15. eLife. 12. 7 indexed citations
10.
Sauvé, Véronique, et al.. (2022). Feedforward activation of PRKN/parkin. Autophagy. 19(2). 729–730. 7 indexed citations
11.
Sauvé, Véronique, et al.. (2022). Structural basis for feedforward control in the PINK1/Parkin pathway. The EMBO Journal. 41(12). e109460–e109460. 20 indexed citations
12.
Poissonnier, Amanda, Jean‐Philippe Guégan, Ha Thanh Nguyen, et al.. (2018). Disrupting the CD95–PLCγ1 interaction prevents Th17-driven inflammation. Nature Chemical Biology. 14(12). 1079–1089. 25 indexed citations
13.
Chen, Yu, et al.. (2018). Structural Studies of Magnesium Transporter CNNM. Biophysical Journal. 114(3). 570a–570a. 1 indexed citations
14.
Sauvé, Véronique, Asparouh Lilov, Marta Vranas, et al.. (2015). A Ubl/ubiquitin switch in the activation of Parkin. The EMBO Journal. 34(20). 2492–2505. 164 indexed citations
15.
Sauvé, Véronique, Karl Grenier, Matthew Y. H. Tang, et al.. (2013). Structure of Parkin Reveals Mechanisms for Ubiquitin Ligase Activation. Science. 340(6139). 1451–1455. 417 indexed citations breakdown →
16.
Jansen, Gregor, Pekka Määttänen, A. Yu. Denisov, et al.. (2012). An Interaction Map of Endoplasmic Reticulum Chaperones and Foldases. Molecular & Cellular Proteomics. 11(9). 710–723. 73 indexed citations
17.
Kozlov, Guennadi & Kalle Gehring. (2010). Molecular Basis of eRF3 Recognition by the MLLE Domain of Poly(A)-Binding Protein. PLoS ONE. 5(4). e10169–e10169. 44 indexed citations
18.
Liu, Qian, et al.. (2010). Apoptotic Regulation by MCL-1 through Heterodimerization. Journal of Biological Chemistry. 285(25). 19615–19624. 57 indexed citations
19.
Denisov, A. Yu., Pekka Määttänen, Tara Sprules, David Y. Thomas, & Kalle Gehring. (2007). 1H, 13C and 15N resonance assignments of the bb′ domains of human protein disulfide isomerase. Biomolecular NMR Assignments. 1(1). 129–130. 4 indexed citations
20.
Ekiel, Irena, Magnus Abrahamson, D. Bruce Fulton, et al.. (1997). NMR structural studies of human cystatin C dimers and monomers. Journal of Molecular Biology. 271(2). 266–277. 93 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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