Austin Clyde
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Protein Structure and Dynamics 4
- Bioinformatics and Genomic Networks 3
- Bacillus and Francisella bacterial research 1
- Gene expression and cancer classification 1
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- Computational Drug Discovery Methods 8
- Co-authors
- Rick Stevens (7 shared papers)Thomas Brettin (4 shared papers)Alexander Partin (4 shared papers)Oleksandr Narykov (3 shared papers)Yitan Zhu (2 shared papers)Jamie Overbeek (2 shared papers)Arvind Ramanathan (6 shared papers)Heng Ma (3 shared papers)
- Journals
- Scientific Reports (1 paper)Journal of Medicinal Chemistry (1 paper)Cancers (1 paper)Cancer Research (1 paper)Patterns (1 paper)
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Austin Clyde
11 papers receiving 162 citations
Peers
Comparison fields: 5 of 57
- Computational Theory and Mathematics 76
- Health Informatics 6
- Infectious Diseases 20
- Information Systems and Management 7
- Molecular Biology 66
Countries citing papers authored by Austin Clyde
This map shows the geographic impact of Austin Clyde'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 Austin Clyde with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Austin Clyde more than expected).
Fields of papers citing papers by Austin Clyde
This network shows the impact of papers produced by Austin Clyde. 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 Austin Clyde. The network helps show where Austin Clyde may publish in the future.
Co-authors
The 25 scholars most cited alongside Austin Clyde, 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 | 65 | |
| 2 | 2021 | 44 | |
| 3 | 2023 | 17 | |
| 4 | 2021 | 9 | |
| 5 | 2023 | 7 | |
| 6 | 2022 | 6 | |
| 7 | 2021 | 6 | |
| 8 | 2021 | 4 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 2 | |
| 11 | 2023 | 1 |
About Austin Clyde
Austin Clyde is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Information Systems and Management and Biophysics, having authored 11 papers that have together received 163 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Machine Learning in Materials Science (4 papers), Protein Structure and Dynamics (4 papers), Bioinformatics and Genomic Networks (3 papers), Scientific Computing and Data Management (2 papers), Cell Image Analysis Techniques (2 papers), Bacillus and Francisella bacterial research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Computational Theory and Mathematics (76 citations), Health Informatics (6 citations), Infectious Diseases (20 citations), Information Systems and Management (7 citations) and Molecular Biology (66 citations). Austin Clyde has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Rick Stevens, Thomas Brettin, Alexander Partin, Oleksandr Narykov, Yitan Zhu, Jamie Overbeek, Arvind Ramanathan, Heng Ma, G.N. Phillips and Hui Li. Their work appears in journals such as Scientific Reports, Journal of Medicinal Chemistry, Cancers, Cancer Research and Patterns.
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.