Prasenjit Mukherjee
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Organic Chemistry
- Public Health, Environmental and Occupational Health
- Infectious Diseases
- Co-authors
- Ingo MueggeÉric MartinPrashant DesaiMitchell A. AveryFalgun ShahBaisakhi ChakrabortyJohanna M. JansenBabu L. Tekwani
- Topics
- Computational Drug Discovery Methods (14 papers)Topic Modeling (6 papers)Natural Language Processing Techniques (6 papers)
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
Prasenjit Mukherjee
45 papers receiving 732 citations
Peers
Comparison fields: 5 of 110
- Computational Theory and Mathematics 404
- Molecular Biology 369
- Organic Chemistry 105
- Public Health, Environmental and Occupational Health 103
- Infectious Diseases 103
Countries citing papers authored by Prasenjit Mukherjee
This map shows the geographic impact of Prasenjit Mukherjee'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 Prasenjit Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prasenjit Mukherjee more than expected).
Fields of papers citing papers by Prasenjit Mukherjee
This network shows the impact of papers produced by Prasenjit Mukherjee. 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 Prasenjit Mukherjee. The network helps show where Prasenjit Mukherjee may publish in the future.
Co-authorship network of co-authors of Prasenjit Mukherjee
This figure shows the co-authorship network connecting the top 25 collaborators of Prasenjit Mukherjee. A scholar is included among the top collaborators of Prasenjit Mukherjee 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 Prasenjit Mukherjee. Prasenjit Mukherjee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 4 | |
| 9 | 41 | |
| 10 | 6 | |
| 11 | 14 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 13 | |
| 15 | 9 | |
| 16 | 8 | |
| 17 | 9 | |
| 18 | 38 | |
| 19 | 28 | |
| 20 | 13 |
About Prasenjit Mukherjee
Prasenjit Mukherjee is a scholar working on Computational Theory and Mathematics, Health Information Management and Infectious Diseases, having authored 47 papers that have together received 751 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (14 papers), Topic Modeling (6 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Computational Theory and Mathematics (404 citations), Infectious Diseases (103 citations) and Molecular Biology (369 citations). Prasenjit Mukherjee has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Ingo Muegge, Éric Martin, Prashant Desai, Mitchell A. Avery, Falgun Shah, Mitchell A. Avery, Baisakhi Chakraborty, Johanna M. Jansen, Babu L. Tekwani and David C. Sullivan. Their work appears in journals such as Journal of Medicinal Chemistry, Current Medicinal Chemistry and Bioorganic & Medicinal 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.