Kevin Hauser
- Molecular Biology top 1%
- Protein Structure and Dynamics 4
- DNA and Nucleic Acid Chemistry 3
- RNA and protein synthesis mechanisms 3
- Diffusion and Search Dynamics 2
- Computational Theory and Mathematics top 0.2%
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research 2
- Toxicology top 2%
- Spectroscopy top 2%
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- Enzyme Structure and Function 2
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- Fungal Plant Pathogen Control 1
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- Sparse and Compressive Sensing Techniques 1
- Co-authors
- Carlos SimmerlingLauren WickstromKoushik KasavajhalaJosh R. DillenMatthew McCallumGyorgy SnellDavid VeeslerDavide Corti
- Journals
- Science (2 papers)Journal of Molecular Biology (2 papers)Journal of Chemical Theory and Computation (2 papers)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Kevin Hauser
13 papers receiving 8.5k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Molecular Biology 5.9k
- Computational Theory and Mathematics 1.2k
- Infectious Diseases 1.0k
- Toxicology 113
- Spectroscopy 477
Countries citing papers authored by Kevin Hauser
This map shows the geographic impact of Kevin Hauser'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 Kevin Hauser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Hauser more than expected).
Fields of papers citing papers by Kevin Hauser
This network shows the impact of papers produced by Kevin Hauser. 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 Kevin Hauser. The network helps show where Kevin Hauser may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kevin Hauser, 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 | 2023 | 10 | |
| 2 | Shifting mutational constraints in the SARS-CoV-2 receptor-binding domain during viral evolutionbreakdown → | 2022 | 157 |
| 3 | Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagementbreakdown → | 2022 | 311 |
| 4 | 2022 | 1 | |
| 5 | 2019 | 68 | |
| 6 | 2018 | 41 | |
| 7 | 2018 | 64 | |
| 8 | 2017 | 8 | |
| 9 | 2015 | 1 | |
| 10 | 2015 | 8 | |
| 11 | 2015 | 2 | |
| 12 | ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SBbreakdown → | 2015 | 7892 |
| 13 | 1974 | 18 |
About Kevin Hauser
Kevin Hauser is a scholar working on Acoustics and Ultrasonics, Biophysics and Molecular Biology, having authored 13 papers that have together received 8.6k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (4 papers), DNA and Nucleic Acid Chemistry (3 papers), RNA and protein synthesis mechanisms (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Diffusion and Search Dynamics (2 papers), Enzyme Structure and Function (2 papers), Fungal Plant Pathogen Control (1 paper) and Sparse and Compressive Sensing Techniques (1 paper). The work is most often cited by research in Molecular Biology (5.9k citations), Computational Theory and Mathematics (1.2k citations) and Infectious Diseases (1.0k citations). Kevin Hauser has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Carlos Simmerling, Lauren Wickstrom, Koushik Kasavajhala, Josh R. Dillen, Matthew McCallum, Gyorgy Snell, David Veesler, Davide Corti, Laura E. Rosen and John E. Bowen. Their work appears in journals such as Science, Journal of Molecular Biology, Journal of Chemical Theory and Computation, MethodsX and Chemical Physics Letters.
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.