Pawan Kumar

43 papers receiving 635 citations

Pawan Kumar's Hit Papers

THPdb: Database of FDA-approved peptide and protein therapeutics 2017 · 365 citations
3650+3+6Years since publication100200300

Peers

Pawan Kumar
Comparison fields: 5 of 118
  • Microbiology 92
  • Computational Theory and Mathematics 108
  • Infectious Diseases 105
  • Pharmaceutical Science 31
  • Molecular Biology 339
Replace Meenu Sharma with:
Meenu Sharma India
Usman Sumo Friend Tambunan Indonesia
Md. Arif Khan Bangladesh
Claudia P. Spampinato Argentina
Subhomoi Borkotoky India
Jin Soo Shin South Korea
Ubolsree Leartsakulpanich Thailand
Chih-Chieh Chen Taiwan
Leena Pohjala Finland
Jiuyu Liu United States
Pawan Kumar relative to Meenu Sharma India Meenu Sharma's profile →
Citations per field
00.5×1.5×
Meenu Sharma · 1×
Citations per year

Countries citing papers authored by Pawan Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Pawan Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pawan Kumar, 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 Pawan Kumar Line = papers co-authored together Pawan Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
THPdb: Database of FDA-approved peptide and protein therapeutics
Hit paper breakdown →
2017365
2 202148
3 201134
4 202229
5 202028
6 201319
7 202417
8 202012
9 20249
10 20248
11 20227
12 20246
13 20175
14 20225
15 20225
16 20234
17 20244
18 20233
19 20233
20 20223

About Pawan Kumar

Pawan Kumar is a scholar working on Plant Science, Infectious Diseases, Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 57 papers that have together received 647 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Smart Agriculture and AI (5 papers), Quality and Supply Management (3 papers), Vehicle License Plate Recognition (2 papers), Stochastic Gradient Optimization Techniques (2 papers), SARS-CoV-2 detection and testing (2 papers) and Sustainable Supply Chain Management (2 papers). The work is most often cited by research in Microbiology (92 citations), Computational Theory and Mathematics (108 citations), Infectious Diseases (105 citations), Pharmaceutical Science (31 citations) and Molecular Biology (339 citations). Pawan Kumar has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include Sandeep Singh, Jesse S. Samuel, Ankur Gautam, Meenu Sharma, Gajendra P. S. Raghava, Salman Sadullah Usmani, Sourav Kalra, Amresh Prakash, Shashikant Ray and Shradha Khater. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Scientific Reports, PLoS ONE, Systematic and Applied Microbiology and SIAM Journal on Optimization.

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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