Umesh Panwar

20 papers receiving 420 citations

Peers

Umesh Panwar
Comparison fields: 5 of 72
  • Computational Theory and Mathematics 188
  • Virology 34
  • Infectious Diseases 107
  • Molecular Biology 203
  • Pharmacology 19
Replace Matteo Pavan with:
Matteo Pavan Italy
Lovika Mittal India
Sathishkumar Chinnasamy India
Olivier Sheik Amamuddy South Africa
Mitul Srivastava India
Salman Ali Khan Pakistan
Jean-Baptiste Mazarati Rwanda
Mutaib M. Mashraqi Saudi Arabia
Michael H. L. Wong United Kingdom
Amar Ajmal Pakistan
Umesh Panwar relative to Matteo Pavan Italy Matteo Pavan's profile →
Citations per field
00.5×8.3×
Matteo Pavan · 1×
Citations per year

Countries citing papers authored by Umesh Panwar

Since Specialization
Citations

This map shows the geographic impact of Umesh Panwar'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 Umesh Panwar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Umesh Panwar more than expected).

Fields of papers citing papers by Umesh Panwar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Umesh Panwar. 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 Umesh Panwar. The network helps show where Umesh Panwar may publish in the future.

Co-authors

The 21 scholars most cited alongside Umesh Panwar, 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 Umesh Panwar Line = papers co-authored together Umesh Panwar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202075
2 202050
3 202146
4 201735
5 202028
6 202126
7 201925
8 201720
9 202019
10 202016
11 201815
12 202313
13 202412
14 201912
15 201811
16 20185
17 20234
18 20244
19 20223
20 20232

About Umesh Panwar

Umesh Panwar is a scholar working on Computational Theory and Mathematics, Molecular Biology, Infectious Diseases, Oncology and Organic Chemistry, having authored 21 papers that have together received 421 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Protein Structure and Dynamics (3 papers), HIV/AIDS drug development and treatment (3 papers), HIV Research and Treatment (3 papers), Synthesis and biological activity (2 papers), RNA and protein synthesis mechanisms (2 papers), Biochemical and Molecular Research (2 papers) and Click Chemistry and Applications (1 paper). The work is most often cited by research in Computational Theory and Mathematics (188 citations), Virology (34 citations), Infectious Diseases (107 citations), Molecular Biology (203 citations) and Pharmacology (19 citations). Umesh Panwar has collaborated with scholars based in India, Saudi Arabia and Czechia. Frequent co-authors include Sanjeev Kumar Singh, Chandrabose Selvaraj, Evžen Bouřa, Dhurvas Chandrasekaran Dinesh, Murali Aarthy, Anuraj Nayarisseri, Vikash Kumar Dubey, Poonam C. Singh, Khushboo Sharma and Tajamul Hussain. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Scientific Reports, Applied Biochemistry and Biotechnology, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Frontiers in Chemistry.

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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