John D. Bickel
Impact in
- Molecular Biology top 10%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Receptor Mechanisms and Signaling
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- Computational Drug Discovery Methods
Papers in
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- Protein Structure and Dynamics 3
- Sphingolipid Metabolism and Signaling 1
- Viral Infectious Diseases and Gene Expression in Insects 1
- vaccines and immunoinformatics approaches 1
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- Computational Drug Discovery Methods 2
- Co-authors
- Angela N. Migues (1 shared paper)He Huang (1 shared paper)Chuan Tian (1 shared paper)Koushik Kasavajhala (1 shared paper)Kellon Belfon (1 shared paper)Lauren Raguette (1 shared paper)Yuzhang Wang (1 shared paper)Qin Wu (1 shared paper)
- Journals
- Journal of Chemical Theory and Computation (2 papers)Journal of Computational Chemistry (2 papers)Bioorganic Chemistry (1 paper)
- Partner nations
- United StatesGermanyEgypt
In The Last Decade
John D. Bickel
4 papers receiving 1.5k citations
John D. Bickel's Hit Papers
Peers
Comparison fields: 5 of 113
- Molecular Biology 1.0k
- Computational Theory and Mathematics 225
- Spectroscopy 116
- Toxicology 20
- Pharmacology 50
Countries citing papers authored by John D. Bickel
This map shows the geographic impact of John D. Bickel'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 John D. Bickel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Bickel more than expected).
Fields of papers citing papers by John D. Bickel
This network shows the impact of papers produced by John D. Bickel. 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 John D. Bickel. The network helps show where John D. Bickel may publish in the future.
Co-authors
The 25 scholars most cited alongside John D. Bickel, 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 | ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution Hit paper breakdown → | 2019 | 1515 |
| 2 | 2022 | 12 | |
| 3 | 2023 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 0 |
About John D. Bickel
John D. Bickel is a scholar working on Molecular Biology, Computational Theory and Mathematics, Spectroscopy, Materials Chemistry and Organic Chemistry, having authored 5 papers that have together received 1.5k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (2 papers), Enzyme Structure and Function (2 papers), Sphingolipid Metabolism and Signaling (1 paper), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Molecular spectroscopy and chirality (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Molecular Biology (1.0k citations), Computational Theory and Mathematics (225 citations), Spectroscopy (116 citations), Toxicology (20 citations) and Pharmacology (50 citations). John D. Bickel has collaborated with scholars based in United States, Germany and Egypt. Frequent co-authors include Angela N. Migues, He Huang, Chuan Tian, Koushik Kasavajhala, Kellon Belfon, Lauren Raguette, Yuzhang Wang, Qin Wu, Carlos Simmerling and Robert C. Rizzo. Their work appears in journals such as Journal of Chemical Theory and Computation, Journal of Computational Chemistry and Bioorganic Chemistry.
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.