Tomer M. Yaron

3.1k total citations
21 papers, 338 citations indexed

About

Tomer M. Yaron is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Tomer M. Yaron has authored 21 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Oncology and 4 papers in Cell Biology. Recurrent topics in Tomer M. Yaron's work include RNA modifications and cancer (4 papers), Advanced Proteomics Techniques and Applications (3 papers) and CRISPR and Genetic Engineering (3 papers). Tomer M. Yaron is often cited by papers focused on RNA modifications and cancer (4 papers), Advanced Proteomics Techniques and Applications (3 papers) and CRISPR and Genetic Engineering (3 papers). Tomer M. Yaron collaborates with scholars based in United States, Israel and France. Tomer M. Yaron's co-authors include Jared L. Johnson, Lewis C. Cantley, Hamootal Duadi, Moti Fridman, Avi Klein, Nathanael S. Gray, Emily M. Huntsman, Zainab M. Doctor, Scott B. Ficarro and Christopher M. Browne and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Tomer M. Yaron

18 papers receiving 333 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomer M. Yaron United States 11 203 63 50 45 39 21 338
Hervé Minoux France 9 460 2.3× 63 1.0× 29 0.6× 53 1.2× 46 1.2× 15 728
Hiroaki Honda Japan 9 128 0.6× 35 0.6× 40 0.8× 25 0.6× 85 2.2× 32 365
Vinay Ayyappan United States 9 221 1.1× 90 1.4× 15 0.3× 73 1.6× 16 0.4× 18 390
Austin Vogt United States 11 517 2.5× 57 0.9× 34 0.7× 84 1.9× 20 0.5× 19 768
Andreas Betz United States 14 165 0.8× 49 0.8× 39 0.8× 65 1.4× 53 1.4× 22 618
Annette Duelli Sweden 10 259 1.3× 22 0.3× 16 0.3× 41 0.9× 23 0.6× 16 414
Axelle Renodon‐Cornière France 17 479 2.4× 153 2.4× 55 1.1× 45 1.0× 11 0.3× 30 633
Devdoot Majumdar United States 10 250 1.2× 37 0.6× 9 0.2× 86 1.9× 26 0.7× 17 431
Masataka Shirai Japan 10 151 0.7× 82 1.3× 13 0.3× 40 0.9× 76 1.9× 29 365

Countries citing papers authored by Tomer M. Yaron

Since Specialization
Citations

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

Fields of papers citing papers by Tomer M. Yaron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tomer M. Yaron. 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 Tomer M. Yaron. The network helps show where Tomer M. Yaron may publish in the future.

Co-authorship network of co-authors of Tomer M. Yaron

This figure shows the co-authorship network connecting the top 25 collaborators of Tomer M. Yaron. A scholar is included among the top collaborators of Tomer M. Yaron 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 Tomer M. Yaron. Tomer M. Yaron 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.
Müller‐Dott, Sophia, Eric J. Jaehnig, Wen Jiang, et al.. (2025). Comprehensive evaluation of phosphoproteomic-based kinase activity inference. Nature Communications. 16(1). 4771–4771.
2.
Jaehnig, Eric J., Yuxing Liao, Zhiao Shi, et al.. (2025). Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites. Nature Communications. 16(1). 2766–2766. 2 indexed citations
3.
Yeung, Wayland, Jingrang Lu, Samiksha Katiyar, et al.. (2025). An atlas of bacterial serine-threonine kinases reveals functional diversity and key distinctions from eukaryotic kinases. Science Signaling. 18(885). eadt8686–eadt8686. 1 indexed citations
4.
Chen, Jun‐Song, et al.. (2024). Substrate displacement of CK1 C-termini regulates kinase specificity. Science Advances. 10(19). eadj5185–eadj5185. 3 indexed citations
5.
Chen, Jun‐Song, et al.. (2024). Abstract 1844 Substrate displacement of CK1 C-termini regulates kinase specificity. Journal of Biological Chemistry. 300(3). 106984–106984.
6.
Tamir, Tigist Y., John M. Asara, Jared L. Johnson, et al.. (2024). Parallel phosphoproteomics and metabolomics map the global metabolic tyrosine phosphoproteome. Proceedings of the National Academy of Sciences. 121(47). e2413837121–e2413837121. 2 indexed citations
7.
Sinha, Niladri K., Ki Hong Nam, Tomer M. Yaron, et al.. (2024). The ribotoxic stress response drives UV-mediated cell death. Cell. 187(14). 3652–3670.e40. 39 indexed citations
8.
Paulo, João A., Tomer M. Yaron, Jared L. Johnson, et al.. (2024). Pleiotropic tumor suppressive functions of PTEN missense mutations during gliomagenesis. iScience. 27(12). 111278–111278.
9.
Nilsson-Payant, Benjamin E., Boris Bonaventure, Chengjin Ye, et al.. (2023). SARS-CoV-2 hijacks p38β/MAPK11 to promote virus replication. mBio. 14(4). e0100723–e0100723. 8 indexed citations
10.
Lin, Kuan‐Ting, Chani Stossel, Zahava Siegfried, et al.. (2023). RBFOX2 modulates a metastatic signature of alternative splicing in pancreatic cancer. Nature. 617(7959). 147–153. 55 indexed citations
11.
Sarraf, Shireen A., Ki Hong Nam, Tomer M. Yaron, et al.. (2023). NAK-associated protein 1/NAP1 activates TBK1 to ensure accurate mitosis and cytokinesis. The Journal of Cell Biology. 223(2). 4 indexed citations
12.
Darabedian, Narek, Mengyang Fan, Hyuk‐Soo Seo, et al.. (2023). Depletion of creatine phosphagen energetics with a covalent creatine kinase inhibitor. Nature Chemical Biology. 19(7). 815–824. 26 indexed citations
13.
Akiyama, Yo, Yifat Geffen, Shankara Anand, et al.. (2022). Abstract 794: Pan-cancer proteogenomic analysis reveals functional mechanisms underlying DNA repair deficiencies. Cancer Research. 82(12_Supplement). 794–794. 1 indexed citations
14.
Robert, Thomas, Jared L. Johnson, Tomer M. Yaron, et al.. (2020). Development of a CDK10/CycM in vitro Kinase Screening Assay and Identification of First Small-Molecule Inhibitors. Frontiers in Chemistry. 8. 147–147. 12 indexed citations
15.
Ferguson, Fleur M., Zainab M. Doctor, Scott B. Ficarro, et al.. (2019). Discovery of Covalent CDK14 Inhibitors with Pan-TAIRE Family Specificity. Cell chemical biology. 26(6). 804–817.e12. 19 indexed citations
16.
Liu, Chunliang, Giselle M. Knudsen, Anthony M. Pedley, et al.. (2019). Mapping Post-Translational Modifications of de Novo Purine Biosynthetic Enzymes: Implications for Pathway Regulation. Journal of Proteome Research. 18(5). 2078–2087. 16 indexed citations
17.
Zheng, Yuxiang, et al.. (2019). Regulation of folate and methionine metabolism by multisite phosphorylation of human methylenetetrahydrofolate reductase. Scientific Reports. 9(1). 28 indexed citations
18.
Browne, Christopher M., Baishan Jiang, Scott B. Ficarro, et al.. (2018). A Chemoproteomic Strategy for Direct and Proteome-Wide Covalent Inhibitor Target-Site Identification. Journal of the American Chemical Society. 141(1). 191–203. 56 indexed citations
19.
Yaron, Tomer M., Avi Klein, Hamootal Duadi, & Moti Fridman. (2017). Temporal superresolution based on a localization microscopy algorithm. Applied Optics. 56(9). D24–D24. 22 indexed citations
20.
Klein, Avi, et al.. (2017). Temporal depth imaging. Optica. 4(5). 502–502. 31 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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