Eric T. Kim
Impact in
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- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Protein Structure and Dynamics
- Protein Kinase Regulation and GTPase Signaling
- Receptor Mechanisms and Signaling
Papers in
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- Protein Structure and Dynamics 4
- Glycosylation and Glycoproteins Research 3
- Protein Kinase Regulation and GTPase Signaling 2
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- Monoclonal and Polyclonal Antibodies Research 5
- Co-authors
- David E. Shaw (10 shared papers)Yibing Shan (9 shared papers)Ron O. Dror (3 shared papers)Michael P. Eastwood (2 shared papers)Markus A. Seeliger (2 shared papers)Anton Arkhipov (4 shared papers)Albert C. Pan (1 shared paper)John Jumper (1 shared paper)
- Journals
- Journal of the American Chemical Society (2 papers)PLoS Computational Biology (2 papers)Proceedings of the National Academy of Sciences (2 papers)Nature Communications (1 paper)Nature Structural & Molecular Biology (1 paper)
- Partner nations
- United StatesRussiaFinland
In The Last Decade
Eric T. Kim
11 papers receiving 1.5k citations
Eric T. Kim's Hit Papers
Peers
Comparison fields: 5 of 110
- Computational Theory and Mathematics 313
- Molecular Biology 1.1k
- Oncology 354
- Genetics 93
- Radiology, Nuclear Medicine and Imaging 190
Countries citing papers authored by Eric T. Kim
This map shows the geographic impact of Eric T. Kim'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 Eric T. Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric T. Kim more than expected).
Fields of papers citing papers by Eric T. Kim
This network shows the impact of papers produced by Eric T. Kim. 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 Eric T. Kim. The network helps show where Eric T. Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric T. Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | How Does a Drug Molecule Find Its Target Binding Site? Hit paper breakdown → | 2011 | 484 |
| 2 | Oncogenic Mutations Counteract Intrinsic Disorder in the EGFR Kinase and Promote Receptor Dimerization Hit paper breakdown → | 2012 | 276 |
| 3 | 2013 | 169 | |
| 4 | 2014 | 122 | |
| 5 | 2007 | 107 | |
| 6 | 2012 | 102 | |
| 7 | 2015 | 98 | |
| 8 | 2013 | 65 | |
| 9 | 2014 | 38 | |
| 10 | 2022 | 29 | |
| 11 | Desmond/GPU Performance as of November 2014 | 2014 | 10 |
About Eric T. Kim
Eric T. Kim is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Oncology, Materials Chemistry and Computational Theory and Mathematics, having authored 11 papers that have together received 1.5k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (5 papers), Protein Structure and Dynamics (4 papers), HER2/EGFR in Cancer Research (3 papers), Enzyme Structure and Function (3 papers), Glycosylation and Glycoproteins Research (3 papers), Computational Drug Discovery Methods (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers) and Cytokine Signaling Pathways and Interactions (1 paper). The work is most often cited by research in Computational Theory and Mathematics (313 citations), Molecular Biology (1.1k citations), Oncology (354 citations), Genetics (93 citations) and Radiology, Nuclear Medicine and Imaging (190 citations). Eric T. Kim has collaborated with scholars based in United States, Russia and Finland. Frequent co-authors include David E. Shaw, Yibing Shan, Ron O. Dror, Michael P. Eastwood, Markus A. Seeliger, Anton Arkhipov, Albert C. Pan, John Jumper, Xuewu Zhang and John Kuriyan. Their work appears in journals such as Journal of the American Chemical Society, PLoS Computational Biology, Proceedings of the National Academy of Sciences, Nature Communications and Nature Structural & Molecular Biology.
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.