Vivek Modi
Impact in
-
- Computational Drug Discovery Methods
-
- Protein Structure and Dynamics
- Protein Kinase Regulation and GTPase Signaling
- Melanoma and MAPK Pathways
- RNA and protein synthesis mechanisms
- PI3K/AKT/mTOR signaling in cancer
Papers in
-
- Cell death mechanisms and regulation 4
- RNA Interference and Gene Delivery 3
- Protein Structure and Dynamics 3
- Lipid Membrane Structure and Behavior 1
-
- Computational Drug Discovery Methods 4
- Co-authors
- Roland L. Dunbrack (8 shared papers)Ronald M. Levy (1 shared paper)Ramachandran Vijayan (1 shared paper)Jeffrey R. Peterson (1 shared paper)Haiching Ma (1 shared paper)Peng He (1 shared paper)Krisna C. Duong‐Ly (1 shared paper)Ramasubbu Sankararamakrishnan (4 shared papers)
- Journals
- Proteins Structure Function and Bioinformatics (4 papers)Scientific Reports (1 paper)Journal of Medicinal Chemistry (1 paper)Journal of Molecular Graphics and Modelling (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Vivek Modi
11 papers receiving 605 citations
Peers
Comparison fields: 5 of 71
- Computational Theory and Mathematics 156
- Molecular Biology 494
- Cell Biology 73
- Oncology 98
- Genetics 34
Countries citing papers authored by Vivek Modi
This map shows the geographic impact of Vivek Modi'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 Vivek Modi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivek Modi more than expected).
Fields of papers citing papers by Vivek Modi
This network shows the impact of papers produced by Vivek Modi. 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 Vivek Modi. The network helps show where Vivek Modi may publish in the future.
Co-authors
The 13 scholars most cited alongside Vivek Modi, 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 | 2019 | 218 | |
| 2 | 2014 | 177 | |
| 3 | 2019 | 81 | |
| 4 | 2021 | 58 | |
| 5 | 2016 | 36 | |
| 6 | 2016 | 27 | |
| 7 | 2012 | 15 | |
| 8 | 2013 | 11 | |
| 9 | 2017 | 8 | |
| 10 | 2016 | 8 | |
| 11 | 2013 | 4 | |
| 12 | 2019 | 0 |
About Vivek Modi
Vivek Modi is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Cell Biology and Surgery, having authored 12 papers that have together received 643 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Cell death mechanisms and regulation (4 papers), RNA Interference and Gene Delivery (3 papers), Enzyme Structure and Function (3 papers), Protein Structure and Dynamics (3 papers), Pancreatic function and diabetes (1 paper), Lipid Membrane Structure and Behavior (1 paper) and Endoplasmic Reticulum Stress and Disease (1 paper). The work is most often cited by research in Computational Theory and Mathematics (156 citations), Molecular Biology (494 citations), Cell Biology (73 citations), Oncology (98 citations) and Genetics (34 citations). Vivek Modi has collaborated with scholars based in United States and India. Frequent co-authors include Roland L. Dunbrack, Ronald M. Levy, Ramachandran Vijayan, Jeffrey R. Peterson, Haiching Ma, Peng He, Krisna C. Duong‐Ly, Ramasubbu Sankararamakrishnan, Dilraj Lama and Qifang Xu. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Scientific Reports, Journal of Medicinal Chemistry, Journal of Molecular Graphics and Modelling and Nucleic Acids Research.
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.