Sandeepkumar Kothiwale
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- vaccines and immunoinformatics approaches
Papers in
-
- Computational Drug Discovery Methods 5
-
- Protein Structure and Dynamics 3
- Protein Degradation and Inhibitors 1
- Bioinformatics and Genomic Networks 1
- Co-authors
- Jens Meiler (6 shared papers)Edward W. Lowe (3 shared papers)Gregory Sliwoski (1 shared paper)Jeffrey Mendenhall (3 shared papers)Corina M. Borza (2 shared papers)Ambra Pozzi (2 shared papers)C. Murali Krishna (1 shared paper)Avinash Ghanate (1 shared paper)
- Journals
- Nature Communications (1 paper)Drug Discovery Today (1 paper)Journal of Chemical Information and Modeling (1 paper)JAMA Network Open (1 paper)Molecules (1 paper)
- Partner nations
- United StatesGermanyIndia
In The Last Decade
Sandeepkumar Kothiwale
8 papers receiving 1.7k citations
Sandeepkumar Kothiwale's Hit Papers
Peers
Comparison fields: 5 of 131
- Computational Theory and Mathematics 787
- Molecular Biology 922
- Pharmacology 110
- Drug Discovery 2
- Biophysics 63
Countries citing papers authored by Sandeepkumar Kothiwale
This map shows the geographic impact of Sandeepkumar Kothiwale'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 Sandeepkumar Kothiwale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandeepkumar Kothiwale more than expected).
Fields of papers citing papers by Sandeepkumar Kothiwale
This network shows the impact of papers produced by Sandeepkumar Kothiwale. 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 Sandeepkumar Kothiwale. The network helps show where Sandeepkumar Kothiwale may publish in the future.
Co-authors
The 25 scholars most cited alongside Sandeepkumar Kothiwale, 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 | Computational Methods in Drug Discovery Hit paper breakdown → | 2014 | 1463 |
| 2 | 2015 | 101 | |
| 3 | 2014 | 71 | |
| 4 | 2011 | 51 | |
| 5 | 2020 | 36 | |
| 6 | 2020 | 28 | |
| 7 | 2022 | 13 | |
| 8 | 2017 | 12 | |
| 9 | 2025 | 0 |
About Sandeepkumar Kothiwale
Sandeepkumar Kothiwale is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Materials Chemistry and Pharmacology, having authored 9 papers that have together received 1.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Click Chemistry and Applications (3 papers), Protein Structure and Dynamics (3 papers), Enzyme Structure and Function (2 papers), Pharmacogenetics and Drug Metabolism (1 paper), Digital Imaging for Blood Diseases (1 paper), Protein Degradation and Inhibitors (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Computational Theory and Mathematics (787 citations), Molecular Biology (922 citations), Pharmacology (110 citations), Drug Discovery (2 citations) and Biophysics (63 citations). Sandeepkumar Kothiwale has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Jens Meiler, Edward W. Lowe, Gregory Sliwoski, Jeffrey Mendenhall, Corina M. Borza, Ambra Pozzi, C. Murali Krishna, Avinash Ghanate, Dominique Bertrand and Surya Pratap Singh. Their work appears in journals such as Nature Communications, Drug Discovery Today, Journal of Chemical Information and Modeling, JAMA Network Open and Molecules.
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.