Pankaj Agarwal
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
Papers in
-
- Computational Drug Discovery Methods 17
- Co-authors
- Lun YangGuanghui HuDilip RajagopalanYong LiMark R. HurleDavid B. SearlsPhilippe SanséauJosep F. Abril
- Journals
- Nature Reviews Drug Discovery (4 papers)PLoS ONE (4 papers)Bioinformatics (3 papers)Drug Discovery Today (3 papers)Scientific Reports (2 papers)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Pankaj Agarwal
77 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 175
- Computational Theory and Mathematics 853
- Computer Graphics and Computer-Aided Design 118
- Molecular Biology 1.8k
- Pharmacology 148
- Microbiology 12
Countries citing papers authored by Pankaj Agarwal
This map shows the geographic impact of Pankaj Agarwal'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 Pankaj Agarwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pankaj Agarwal more than expected).
Fields of papers citing papers by Pankaj Agarwal
This network shows the impact of papers produced by Pankaj Agarwal. 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 Pankaj Agarwal. The network helps show where Pankaj Agarwal may publish in the future.
Co-authors
The 25 scholars most cited alongside Pankaj Agarwal, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2019 | 7 | |
| 4 | 2018 | 13 | |
| 5 | 2017 | 12 | |
| 6 | Prediction of Secondary Structure of Protein Using Support Vector Machine | 2014 | 0 |
| 7 | 2013 | 9 | |
| 8 | 2013 | 7 | |
| 9 | 2013 | 1 | |
| 10 | 2012 | 3 | |
| 11 | 2012 | 11 | |
| 12 | 2011 | 34 | |
| 13 | 2011 | 190 | |
| 14 | 2009 | 80 | |
| 15 | 2008 | 12 | |
| 16 | 2002 | 8 | |
| 17 | I/O-Efficient Algorithms for Contour-line Extraction and Planar Graph Blocking (Extended Abstract). | 1998 | 1 |
| 18 | Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective | 1998 | 1 |
| 19 | 1996 | 16 | |
| 20 | 1970 | 16 |
About Pankaj Agarwal
Pankaj Agarwal is a scholar working on Microbiology, Computational Theory and Mathematics, Molecular Biology, Computer Graphics and Computer-Aided Design and Business and International Management, having authored 81 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (19 papers), Computational Drug Discovery Methods (17 papers), Gene expression and cancer classification (12 papers), Genomics and Phylogenetic Studies (9 papers), Machine Learning in Bioinformatics (8 papers), RNA and protein synthesis mechanisms (6 papers), Pharmacogenetics and Drug Metabolism (4 papers) and Cellular Mechanics and Interactions (4 papers). The work is most often cited by research in Computational Theory and Mathematics (853 citations), Computer Graphics and Computer-Aided Design (118 citations), Molecular Biology (1.8k citations), Pharmacology (148 citations) and Microbiology (12 citations). Pankaj Agarwal has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Lun Yang, Guanghui Hu, Dilip Rajagopalan, Yong Li, Mark R. Hurle, David B. Searls, Philippe Sanséau, Josep F. Abril, Roderic Guigó and David J. States. Their work appears in journals such as Nature Reviews Drug Discovery, PLoS ONE, Bioinformatics, Drug Discovery Today and Scientific Reports.
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.