Claudio N. Cavasotto
- Molecular Biology top 2%
- Computational Theory and Mathematics top 0.2%
- Organic Chemistry top 5%
- Materials Chemistry top 10%
- Pharmacology top 5%
- Co-authors
- Ruben AbagyanSharangdhar S. PhatakAndrew OrryJuan I. Di FilippoValeria ScardinoJulio KovacsNatalia S. AdlerFrancesca Spyrakis
- Topics
- Computational Drug Discovery Methods (39 papers)Protein Structure and Dynamics (20 papers)Receptor Mechanisms and Signaling (14 papers)
- Partner nations
- United StatesArgentinaSpain
In The Last Decade
Claudio N. Cavasotto
83 papers receiving 4.0k citations
Peers
Comparison fields: 5 of 150
- Molecular Biology 2.7k
- Computational Theory and Mathematics 1.8k
- Organic Chemistry 576
- Materials Chemistry 431
- Pharmacology 349
Countries citing papers authored by Claudio N. Cavasotto
This map shows the geographic impact of Claudio N. Cavasotto'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 Claudio N. Cavasotto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudio N. Cavasotto more than expected).
Fields of papers citing papers by Claudio N. Cavasotto
This network shows the impact of papers produced by Claudio N. Cavasotto. 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 Claudio N. Cavasotto. The network helps show where Claudio N. Cavasotto may publish in the future.
Co-authorship network of co-authors of Claudio N. Cavasotto
This figure shows the co-authorship network connecting the top 25 collaborators of Claudio N. Cavasotto. A scholar is included among the top collaborators of Claudio N. Cavasotto 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 Claudio N. Cavasotto. Claudio N. Cavasotto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 23 | |
| 3 | 31 | |
| 4 | 36 | |
| 5 | 29 | |
| 6 | 63 | |
| 7 | 14 | |
| 8 | 21 | |
| 9 | 21 | |
| 10 | 2 | |
| 11 | 36 | |
| 12 | 24 | |
| 13 | 69 | |
| 14 | 79 | |
| 15 | 31 | |
| 16 | 197 | |
| 17 | 61 | |
| 18 | 54 | |
| 19 | 63 | |
| 20 | 1 |
About Claudio N. Cavasotto
Claudio N. Cavasotto is a scholar working on Computational Theory and Mathematics, Molecular Biology and Organic Chemistry, having authored 85 papers that have together received 4.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (39 papers), Protein Structure and Dynamics (20 papers) and Receptor Mechanisms and Signaling (14 papers). The work is most often cited by research in Computational Theory and Mathematics (1.8k citations), Molecular Biology (2.7k citations) and Pharmacology (349 citations). Claudio N. Cavasotto has collaborated with scholars based in United States, Argentina and Spain. Frequent co-authors include Ruben Abagyan, Sharangdhar S. Phatak, Andrew Orry, Juan I. Di Filippo, Valeria Scardino, Julio Kovacs, Natalia S. Adler, Francesca Spyrakis, Michael J. Garabedian and Victor M. Anisimov. Their work appears in journals such as Journal of the American Chemical Society, Nucleic Acids Research and PLoS ONE.
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.