David J. Huggins
- Molecular Biology top 5%
- Computational Theory and Mathematics top 1%
- Materials Chemistry
- Cell Biology top 5%
- Organic Chemistry top 10%
- Co-authors
- Bruce TidorWoody ShermanDavid R. SpringGuy H. GrantAshok R. VenkitaramanM. C. PayneGrahame J. McKenzieSiniša Vukovič
- Topics
- Protein Structure and Dynamics (24 papers)Computational Drug Discovery Methods (18 papers)Spectroscopy and Quantum Chemical Studies (10 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyAngewandte Chemie International Edition
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
David J. Huggins
61 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 139
- Molecular Biology 1.4k
- Computational Theory and Mathematics 468
- Materials Chemistry 258
- Cell Biology 231
- Organic Chemistry 215
Countries citing papers authored by David J. Huggins
This map shows the geographic impact of David J. Huggins'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 David J. Huggins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Huggins more than expected).
Fields of papers citing papers by David J. Huggins
This network shows the impact of papers produced by David J. Huggins. 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 David J. Huggins. The network helps show where David J. Huggins may publish in the future.
Co-authorship network of co-authors of David J. Huggins
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Huggins. A scholar is included among the top collaborators of David J. Huggins based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David J. Huggins. David J. Huggins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 45 | |
| 5 | 69 | |
| 6 | 9 | |
| 7 | 7 | |
| 8 | 17 | |
| 9 | 5 | |
| 10 | 29 | |
| 11 | 83 | |
| 12 | 41 | |
| 13 | 12 | |
| 14 | 31 | |
| 15 | 12 | |
| 16 | 58 | |
| 17 | 25 | |
| 18 | 34 | |
| 19 | 26 | |
| 20 | 8 |
About David J. Huggins
David J. Huggins is a scholar working on Computational Theory and Mathematics, Molecular Biology and Spectroscopy, having authored 63 papers that have together received 2.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (24 papers), Computational Drug Discovery Methods (18 papers) and Spectroscopy and Quantum Chemical Studies (10 papers). The work is most often cited by research in Computational Theory and Mathematics (468 citations), Molecular Biology (1.4k citations) and Cell Biology (231 citations). David J. Huggins has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Bruce Tidor, Woody Sherman, David R. Spring, Guy H. Grant, Ashok R. Venkitaraman, M. C. Payne, Grahame J. McKenzie, Siniša Vukovič, Malcolm M. Campbell and Christian Dubos. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Angewandte Chemie International Edition.
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.