Tanja Kortemme
- Molecular Biology top 0.5%
- Protein Structure and Dynamics 65
- RNA and protein synthesis mechanisms 34
- Bioinformatics and Genomic Networks 10
- Receptor Mechanisms and Signaling 8
- CRISPR and Genetic Engineering 7
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 9
- Materials Chemistry top 2%
- Enzyme Structure and Function 35
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- Monoclonal and Polyclonal Antibodies Research 5
- Cell Biology top 1%
- Co-authors
- David BakerAlexandre V. MorozovColin A. SmithAvijit ChakrabarttyRobert L. BaldwinThomas E. CreightonDavid E. KimDaniel J. Mandell
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Tanja Kortemme
100 papers receiving 10.9k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Molecular Biology 9.1k
- Computational Theory and Mathematics 902
- Materials Chemistry 2.6k
- Radiology, Nuclear Medicine and Imaging 1.1k
- Cell Biology 768
Countries citing papers authored by Tanja Kortemme
This map shows the geographic impact of Tanja Kortemme'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 Tanja Kortemme with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tanja Kortemme more than expected).
Fields of papers citing papers by Tanja Kortemme
This network shows the impact of papers produced by Tanja Kortemme. 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 Tanja Kortemme. The network helps show where Tanja Kortemme may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tanja Kortemme, 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 | 2025 | 10 | |
| 2 | 2023 | 20 | |
| 3 | 2023 | 11 | |
| 4 | 2022 | 2 | |
| 5 | 2022 | 6 | |
| 6 | 2021 | 3 | |
| 7 | 2021 | 28 | |
| 8 | 2021 | 12 | |
| 9 | 2020 | 58 | |
| 10 | 2020 | 21 | |
| 11 | 2020 | 160 | |
| 12 | 2019 | 147 | |
| 13 | 2019 | 29 | |
| 14 | 2019 | 92 | |
| 15 | 2018 | 158 | |
| 16 | The Rosetta All-Atom Energy Function for Macromolecular Modeling and Designbreakdown → | 2017 | 942 |
| 17 | 2017 | 70 | |
| 18 | 2012 | 80 | |
| 19 | SAT-based protein design | 2009 | 7 |
| 20 | 2006 | 116 |
About Tanja Kortemme
Tanja Kortemme is a scholar working on Molecular Biology, Materials Chemistry and Structural Biology, having authored 100 papers that have together received 11.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (65 papers), Enzyme Structure and Function (35 papers), RNA and protein synthesis mechanisms (34 papers), Bioinformatics and Genomic Networks (10 papers), Computational Drug Discovery Methods (9 papers), Receptor Mechanisms and Signaling (8 papers), CRISPR and Genetic Engineering (7 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). The work is most often cited by research in Molecular Biology (9.1k citations), Computational Theory and Mathematics (902 citations) and Materials Chemistry (2.6k citations). Tanja Kortemme has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include David Baker, Alexandre V. Morozov, Colin A. Smith, Avijit Chakrabartty, Robert L. Baldwin, Thomas E. Creighton, David E. Kim, Daniel J. Mandell, Marina Ramı́rez-Alvarado and Brian Kuhlman. Their work appears in journals such as Nature, Science and Cell.
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.