Pavan Kumar Behara
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Materials Science
Papers in
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- Machine Learning in Materials Science 5
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- Protein Structure and Dynamics 6
- Co-authors
- Joshua T. Horton (6 shared papers)John D. Chodera (5 shared papers)David Dotson (5 shared papers)David L. Mobley (7 shared papers)Daniel J. Cole (6 shared papers)Simon Boothroyd (5 shared papers)Yuanqing Wang (3 shared papers)Trevor Gokey (4 shared papers)
- Journals
- The Journal of Physical Chemistry B (2 papers)Biophysical Journal (1 paper)International Journal of Mineral Processing (1 paper)Chemical Science (1 paper)Scientific Data (1 paper)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Pavan Kumar Behara
11 papers receiving 353 citations
Pavan Kumar Behara's Hit Papers
Peers
Comparison fields: 5 of 79
- Computational Theory and Mathematics 136
- Materials Chemistry 206
- Physical and Theoretical Chemistry 26
- Molecular Biology 154
- Spectroscopy 30
Countries citing papers authored by Pavan Kumar Behara
This map shows the geographic impact of Pavan Kumar Behara'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 Pavan Kumar Behara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavan Kumar Behara more than expected).
Fields of papers citing papers by Pavan Kumar Behara
This network shows the impact of papers produced by Pavan Kumar Behara. 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 Pavan Kumar Behara. The network helps show where Pavan Kumar Behara may publish in the future.
Co-authors
The 25 scholars most cited alongside Pavan Kumar Behara, 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 | Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field Hit paper breakdown → | 2023 | 111 |
| 2 | SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Hit paper breakdown → | 2023 | 104 |
| 3 | 2022 | 35 | |
| 4 | 2013 | 30 | |
| 5 | 2024 | 22 | |
| 6 | 2024 | 15 | |
| 7 | 2019 | 15 | |
| 8 | 2023 | 13 | |
| 9 | 2018 | 11 | |
| 10 | 2024 | 6 | |
| 11 | 2023 | 1 |
About Pavan Kumar Behara
Pavan Kumar Behara is a scholar working on Materials Chemistry, Molecular Biology, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics and Physical and Theoretical Chemistry, having authored 11 papers that have together received 363 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Machine Learning in Materials Science (5 papers), Computational Drug Discovery Methods (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Advanced Chemical Physics Studies (1 paper), Software Testing and Debugging Techniques (1 paper), Spectroscopy and Quantum Chemical Studies (1 paper) and Photochemistry and Electron Transfer Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (136 citations), Materials Chemistry (206 citations), Physical and Theoretical Chemistry (26 citations), Molecular Biology (154 citations) and Spectroscopy (30 citations). Pavan Kumar Behara has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Joshua T. Horton, John D. Chodera, David Dotson, David L. Mobley, Daniel J. Cole, Simon Boothroyd, Yuanqing Wang, Trevor Gokey, Jeffrey Wagner and John E. Herr. Their work appears in journals such as The Journal of Physical Chemistry B, Biophysical Journal, International Journal of Mineral Processing, Chemical Science and Scientific Data.
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.