Tanuj Sharma
Impact in
-
- Computational Drug Discovery Methods
Papers in
-
- Computational Drug Discovery Methods 10
- Co-authors
- Mohammad Imran SiddiqiMohammad Hassan BaigSunil Kumar SinghRenu TripathiJae-June DongKoneni V. SashidharaJerzy GieleckiMarios Loukas
- Journals
- Molecules (2 papers)Molecular Informatics (2 papers)Scientific Reports (1 paper)International Journal of Biological Macromolecules (1 paper)Saudi Pharmaceutical Journal (1 paper)
- Partner nations
- IndiaSouth KoreaUnited States
In The Last Decade
Tanuj Sharma
34 papers receiving 582 citations
Peers
Comparison fields: 5 of 104
- Aging 16
- Computational Theory and Mathematics 117
- Biological Psychiatry 11
- Public Health, Environmental and Occupational Health 123
- Hardware and Architecture 28
Countries citing papers authored by Tanuj Sharma
This map shows the geographic impact of Tanuj Sharma'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 Tanuj Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tanuj Sharma more than expected).
Fields of papers citing papers by Tanuj Sharma
This network shows the impact of papers produced by Tanuj Sharma. 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 Tanuj Sharma. The network helps show where Tanuj Sharma may publish in the future.
Co-authors
The 25 scholars most cited alongside Tanuj Sharma, 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 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2022 | 10 | |
| 4 | 2022 | 12 | |
| 5 | 2022 | 0 | |
| 6 | 2021 | 10 | |
| 7 | 2021 | 20 | |
| 8 | 2020 | 10 | |
| 9 | 2019 | 8 | |
| 10 | 2018 | 23 | |
| 11 | 2018 | 3 | |
| 12 | 2018 | 30 | |
| 13 | 2017 | 18 | |
| 14 | 2017 | 15 | |
| 15 | 2017 | 33 | |
| 16 | 2017 | 16 | |
| 17 | 2017 | 25 | |
| 18 | 2016 | 38 | |
| 19 | 2015 | 20 | |
| 20 | 2010 | 10 |
About Tanuj Sharma
Tanuj Sharma is a scholar working on Biological Psychiatry, Computational Theory and Mathematics, Aging, Infectious Diseases and Toxicology, having authored 36 papers that have together received 586 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Cholinesterase and Neurodegenerative Diseases (4 papers), Malaria Research and Control (4 papers), vaccines and immunoinformatics approaches (3 papers), Protein Structure and Dynamics (2 papers), Research on Leishmaniasis Studies (2 papers) and Trypanosoma species research and implications (2 papers). The work is most often cited by research in Aging (16 citations), Computational Theory and Mathematics (117 citations), Biological Psychiatry (11 citations), Public Health, Environmental and Occupational Health (123 citations) and Hardware and Architecture (28 citations). Tanuj Sharma has collaborated with scholars based in India, South Korea and United States. Frequent co-authors include Mohammad Imran Siddiqi, Mohammad Hassan Baig, Sunil Kumar Singh, Renu Tripathi, Jae-June Dong, Koneni V. Sashidhara, Jerzy Gielecki, Marios Loukas, R. Shane Tubbs and Mohammad Mahtab Alam. Their work appears in journals such as Molecules, Molecular Informatics, Scientific Reports, International Journal of Biological Macromolecules and Saudi Pharmaceutical Journal.
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.