Kenneth Borrelli
Impact in
-
- Computational Drug Discovery Methods
- Structural Biology top 10%
Papers in
-
- Protein Structure and Dynamics 4
- RNA and protein synthesis mechanisms 3
- Chemical Synthesis and Analysis 2
-
- Computational Drug Discovery Methods 7
- Co-authors
- Vı́ctor Guallar (6 shared papers)Kai Zhu (3 shared papers)Robert Abel (4 shared papers)Tyler Day (3 shared papers)Jeremy R. Greenwood (1 shared paper)Ramy Farid (1 shared paper)Edward Harder (1 shared paper)Andreas Vitalis (1 shared paper)
- Journals
- Journal of Chemical Theory and Computation (4 papers)Journal of Chemical Information and Modeling (3 papers)Proceedings of the National Academy of Sciences (2 papers)Structure (2 papers)Journal of Computational Chemistry (1 paper)
- Partner nations
- United StatesSpainFrance
In The Last Decade
Kenneth Borrelli
17 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 106
- Computational Theory and Mathematics 399
- Structural Biology 25
- Molecular Biology 943
- Organic Chemistry 263
- Pharmacology 88
Countries citing papers authored by Kenneth Borrelli
This map shows the geographic impact of Kenneth Borrelli'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 Kenneth Borrelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kenneth Borrelli more than expected).
Fields of papers citing papers by Kenneth Borrelli
This network shows the impact of papers produced by Kenneth Borrelli. 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 Kenneth Borrelli. The network helps show where Kenneth Borrelli may publish in the future.
Co-authors
The 25 scholars most cited alongside Kenneth Borrelli, 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 | 2014 | 353 | |
| 2 | 2005 | 188 | |
| 3 | 2014 | 127 | |
| 4 | 2021 | 118 | |
| 5 | 2012 | 99 | |
| 6 | 2011 | 60 | |
| 7 | 2009 | 57 | |
| 8 | 2020 | 48 | |
| 9 | 2021 | 47 | |
| 10 | 2008 | 45 | |
| 11 | 2018 | 44 | |
| 12 | 2022 | 39 | |
| 13 | 2005 | 35 | |
| 14 | 2021 | 29 | |
| 15 | 2014 | 27 | |
| 16 | 2015 | 24 | |
| 17 | 2022 | 24 |
About Kenneth Borrelli
Kenneth Borrelli is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Organic Chemistry and Pharmacology, having authored 17 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Protein Structure and Dynamics (4 papers), Click Chemistry and Applications (3 papers), RNA and protein synthesis mechanisms (3 papers), Machine Learning in Materials Science (3 papers), Advanced Electron Microscopy Techniques and Applications (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (399 citations), Structural Biology (25 citations), Molecular Biology (943 citations), Organic Chemistry (263 citations) and Pharmacology (88 citations). Kenneth Borrelli has collaborated with scholars based in United States, Spain and France. Frequent co-authors include Vı́ctor Guallar, Kai Zhu, Robert Abel, Tyler Day, Jeremy R. Greenwood, Ramy Farid, Edward Harder, Andreas Vitalis, Gydo C. P. van Zundert and Matthew P. Jacobson. Their work appears in journals such as Journal of Chemical Theory and Computation, Journal of Chemical Information and Modeling, Proceedings of the National Academy of Sciences, Structure and Journal of Computational Chemistry.
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.