Vivek Modi

1.2k citations
13 papers · 675 · h-index 9

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
    • Ubiquitin and proteasome pathways 1
    • Glycosylation and Glycoproteins Research 1
    • Computational Drug Discovery Methods 4

Vivek Modi

12 papers receiving 633 citations

Peers

Vivek Modi
Comparison fields: 5 of 71
  • Computational Theory and Mathematics 155
  • Molecular Biology 506
  • Cell Biology 75
  • Genetics 37
  • Oncology 93
Replace P. Rellos with:
P. Rellos United Kingdom
Dalia I. Hammoudeh United States
Jason Cellitti United States
Alexander Gozman United States
Lalima G. Ahuja United States
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Benedict‐Tilman Berger Germany
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Citations per field
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Citations per year

Countries citing papers authored by Vivek Modi

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Vivek Modi Line = papers co-authored together Vivek Modi links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2019228
2 2014184
3 201985
4 202163
5 201637
6 201628
7 201215
8 201311
9 20169
10 20178
11 20135
12 20132
13 20190

About Vivek Modi

Vivek Modi is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Cell Biology and Surgery, having authored 13 papers that have together received 675 indexed citations. Recurring topics across this work include Cell death mechanisms and regulation (4 papers), Computational Drug Discovery Methods (4 papers), Enzyme Structure and Function (3 papers), RNA Interference and Gene Delivery (3 papers), Protein Structure and Dynamics (3 papers), Ubiquitin and proteasome pathways (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Endoplasmic Reticulum Stress and Disease (1 paper). The work is most often cited by research in Computational Theory and Mathematics (155 citations), Molecular Biology (506 citations), Cell Biology (75 citations), Genetics (37 citations) and Oncology (93 citations). Vivek Modi has collaborated with scholars based in United States, India and Singapore. Frequent co-authors include Roland L. Dunbrack, Jeffrey R. Peterson, Peng He, Ramachandran Vijayan, Ronald M. Levy, Krisna C. Duong‐Ly, Haiching Ma, Ramasubbu Sankararamakrishnan, Qifang Xu and Dilraj Lama. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Scientific Reports, Proceedings of the National Academy of Sciences, Journal of Medicinal Chemistry and Journal of Molecular Graphics and Modelling.

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.

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