Ajit Jadhav
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Molecular Biology top 1%
- Epigenetics and DNA Methylation
- DNA Repair Mechanisms
- Ubiquitin and proteasome pathways
- Histone Deacetylase Inhibitors Research
- Cancer-related gene regulation
- Protein Degradation and Inhibitors
- Cancer therapeutics and mechanisms
Papers in
-
- Computational Drug Discovery Methods 26
- Co-authors
- Anton SimeonovChristopher P. AustinJames IngleseDavid J. MaloneyAdam YasgarDouglas S. AuldNoel SouthallWei Zheng
- Journals
- Journal of Medicinal Chemistry (19 papers)PLoS ONE (13 papers)Scientific Reports (5 papers)Bioorganic & Medicinal Chemistry Letters (5 papers)Biochemistry (4 papers)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
Ajit Jadhav
148 papers receiving 8.0k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Computational Theory and Mathematics 1.3k
- Molecular Biology 5.1k
- Toxicology 169
- Biophysics 233
- Oncology 1.0k
Countries citing papers authored by Ajit Jadhav
This map shows the geographic impact of Ajit Jadhav'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 Ajit Jadhav with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ajit Jadhav more than expected).
Fields of papers citing papers by Ajit Jadhav
This network shows the impact of papers produced by Ajit Jadhav. 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 Ajit Jadhav. The network helps show where Ajit Jadhav may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ajit Jadhav, 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 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2021 | 19 | |
| 4 | 2021 | 36 | |
| 5 | 2020 | 33 | |
| 6 | 2020 | 25 | |
| 7 | 2019 | 10 | |
| 8 | 2019 | 6 | |
| 9 | 2019 | 5 | |
| 10 | 2018 | 31 | |
| 11 | 2018 | 13 | |
| 12 | 2014 | 17 | |
| 13 | 2012 | 31 | |
| 14 | 2009 | 68 | |
| 15 | 2009 | 76 | |
| 16 | 2009 | 11 | |
| 17 | 2009 | 24 | |
| 18 | 2008 | 108 | |
| 19 | 2008 | 16 | |
| 20 | Quantitative high-throughput screening: A titration-based approach that efficiently identifies biological activities in large chemical libraries Hit paper breakdown → | 2006 | 623 |
About Ajit Jadhav
Ajit Jadhav is a scholar working on Toxicology, Computational Theory and Mathematics, Molecular Biology, Pharmacology and Parasitology, having authored 150 papers that have together received 8.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (26 papers), DNA Repair Mechanisms (14 papers), Inflammatory mediators and NSAID effects (11 papers), Epigenetics and DNA Methylation (10 papers), Histone Deacetylase Inhibitors Research (9 papers), Protein Degradation and Inhibitors (9 papers), Ubiquitin and proteasome pathways (8 papers) and Cancer therapeutics and mechanisms (8 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Molecular Biology (5.1k citations), Toxicology (169 citations), Biophysics (233 citations) and Oncology (1.0k citations). Ajit Jadhav has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Anton Simeonov, Christopher P. Austin, James Inglese, David J. Maloney, Adam Yasgar, Douglas S. Auld, Noel Southall, Wei Zheng, Ruili Huang and Ganesha Rai. Their work appears in journals such as Journal of Medicinal Chemistry, PLoS ONE, Scientific Reports, Bioorganic & Medicinal Chemistry Letters and Biochemistry.
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.