Michael C. Cavalier
Impact in
- Biochemistry top 10%
- Antioxidant Activity and Oxidative Stress
Papers in
-
- S100 Proteins and Annexins 5
- Heat shock proteins research 3
- Glycosylation and Glycoproteins Research 2
-
- Computational Drug Discovery Methods 5
- Co-authors
- David J. Weber (6 shared papers)David B. Neau (4 shared papers)M. Chiara Manzini (1 shared paper)Wayne A. Hendrickson (1 shared paper)Paul T. Wilder (5 shared papers)Youn‐Kyung Kim (1 shared paper)Oliver B. Clarke (1 shared paper)Yunting Chen (1 shared paper)
- Journals
- PLoS ONE (3 papers)HortScience (2 papers)Organic & Biomolecular Chemistry (1 paper)Journal of Medicinal Chemistry (1 paper)Analytical Biochemistry (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Michael C. Cavalier
14 papers receiving 321 citations
Peers
Comparison fields: 5 of 75
- Biochemistry 42
- Structural Biology 9
- Molecular Biology 228
- Microbiology 18
- Cancer Research 31
Countries citing papers authored by Michael C. Cavalier
This map shows the geographic impact of Michael C. Cavalier'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 Michael C. Cavalier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael C. Cavalier more than expected).
Fields of papers citing papers by Michael C. Cavalier
This network shows the impact of papers produced by Michael C. Cavalier. 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 Michael C. Cavalier. The network helps show where Michael C. Cavalier may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael C. Cavalier, 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 | 2016 | 115 | |
| 2 | 2018 | 64 | |
| 3 | 2014 | 34 | |
| 4 | 2011 | 21 | |
| 5 | 2015 | 16 | |
| 6 | 2012 | 15 | |
| 7 | 2016 | 15 | |
| 8 | 2007 | 12 | |
| 9 | 2016 | 11 | |
| 10 | 2006 | 8 | |
| 11 | 2006 | 7 | |
| 12 | 2011 | 4 | |
| 13 | 2021 | 2 | |
| 14 | 1976 | 2 | |
| 15 | 2015 | 0 |
About Michael C. Cavalier
Michael C. Cavalier is a scholar working on Molecular Biology, Computational Theory and Mathematics, Biochemistry, Materials Chemistry and Pharmacology, having authored 15 papers that have together received 326 indexed citations. Recurring topics across this work include S100 Proteins and Annexins (5 papers), Computational Drug Discovery Methods (5 papers), Heat shock proteins research (3 papers), Antioxidant Activity and Oxidative Stress (3 papers), Glycosylation and Glycoproteins Research (2 papers), Enzyme Structure and Function (2 papers), Cancer, Hypoxia, and Metabolism (2 papers) and Microbial Natural Products and Biosynthesis (2 papers). The work is most often cited by research in Biochemistry (42 citations), Structural Biology (9 citations), Molecular Biology (228 citations), Microbiology (18 citations) and Cancer Research (31 citations). Michael C. Cavalier has collaborated with scholars based in United States and South Korea. Frequent co-authors include David J. Weber, David B. Neau, M. Chiara Manzini, Wayne A. Hendrickson, Paul T. Wilder, Youn‐Kyung Kim, Oliver B. Clarke, Yunting Chen, Loredana Quadro and Jonathan Kim. Their work appears in journals such as PLoS ONE, HortScience, Organic & Biomolecular Chemistry, Journal of Medicinal Chemistry and Analytical Biochemistry.
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.