Mike J. Bodkin
- Molecular Biology
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Cellular and Molecular Neuroscience
- Spectroscopy
- Co-authors
- Alexander HeifetzPhilip C. BigginMatteo AldeghiDmitri G. FedorovEwa I. ChudykMichelle SoutheyAndrea Townsend‐NicholsonIñaki Morao
- Topics
- Receptor Mechanisms and Signaling (10 papers)Computational Drug Discovery Methods (8 papers)Neuropeptides and Animal Physiology (8 papers)
- Journals
- Journal of Medicinal ChemistryJournal of Computational ChemistryJournal of Chemical Theory and Computation
- Partner nations
- United KingdomJapanUnited States
In The Last Decade
Mike J. Bodkin
14 papers receiving 418 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 328
- Computational Theory and Mathematics 207
- Materials Chemistry 78
- Cellular and Molecular Neuroscience 60
- Spectroscopy 59
Countries citing papers authored by Mike J. Bodkin
This map shows the geographic impact of Mike J. Bodkin'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 Mike J. Bodkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mike J. Bodkin more than expected).
Fields of papers citing papers by Mike J. Bodkin
This network shows the impact of papers produced by Mike J. Bodkin. 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 Mike J. Bodkin. The network helps show where Mike J. Bodkin may publish in the future.
Co-authorship network of co-authors of Mike J. Bodkin
This figure shows the co-authorship network connecting the top 25 collaborators of Mike J. Bodkin. A scholar is included among the top collaborators of Mike J. Bodkin 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 Mike J. Bodkin. Mike J. Bodkin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 9 | |
| 3 | 50 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 14 | |
| 7 | 40 | |
| 8 | 21 | |
| 9 | 14 | |
| 10 | 44 | |
| 11 | 10 | |
| 12 | 24 | |
| 13 | 64 | |
| 14 | 28 | |
| 15 | 90 |
About Mike J. Bodkin
Mike J. Bodkin is a scholar working on Computational Theory and Mathematics, Cellular and Molecular Neuroscience and Molecular Biology, having authored 15 papers that have together received 420 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (10 papers), Computational Drug Discovery Methods (8 papers) and Neuropeptides and Animal Physiology (8 papers). The work is most often cited by research in Computational Theory and Mathematics (207 citations), Molecular Biology (328 citations) and Spectroscopy (59 citations). Mike J. Bodkin has collaborated with scholars based in United Kingdom, Japan and United States. Frequent co-authors include Alexander Heifetz, Philip C. Biggin, Matteo Aldeghi, Dmitri G. Fedorov, Ewa I. Chudyk, Michelle Southey, Andrea Townsend‐Nicholson, Iñaki Morao, Vadim Cherezov and Andrew Anighoro. Their work appears in journals such as Journal of Medicinal Chemistry, Journal of Computational Chemistry and Journal of Chemical Theory and Computation.
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.