Prateek Kumar

1.2k citations
45 papers · 793 · h-index 19

Impact in

  • Aging top 5%
    • Genetics, Aging, and Longevity in Model Organisms
    • SARS-CoV-2 and COVID-19 Research
    • Viral Infections and Vectors

Papers in

Prateek Kumar

44 papers receiving 786 citations

Peers

Prateek Kumar
Comparison fields: 5 of 101
  • Aging 54
  • Infectious Diseases 229
  • Virology 28
  • Public Health, Environmental and Occupational Health 146
  • Molecular Biology 380
Replace Jan Šilhán with:
Jan Šilhán Czechia
Md. Zubbair Malik India
Xavier C. Ding Switzerland
Ítalo Faria do Valle Italy
Jianzhong Cao China
Jonathan Cechetto South Korea
Ákos Putics Hungary
Ashok Kumar Patel India
Liangliang Kong China
Elizabeth Bilsland United Kingdom
Prateek Kumar relative to Jan Šilhán Czechia Jan Šilhán's profile →
Citations per field
00.5×3.6×
Jan Šilhán · 1×
Citations per year

Countries citing papers authored by Prateek Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Prateek Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202085
2 201077
3 201734
4 202033
5 202030
6 202130
7 202028
8 201927
9 202326
10 202126
11 202026
12 202225
13 201924
14 202120
15 202020
16 201919
17 202019
18 202019
19 202018
20 202017

About Prateek Kumar

Prateek Kumar is a scholar working on Molecular Biology, Infectious Diseases, Public Health, Environmental and Occupational Health, Computational Theory and Mathematics and Virology, having authored 45 papers that have together received 793 indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (11 papers), Computational Drug Discovery Methods (10 papers), SARS-CoV-2 and COVID-19 Research (8 papers), HIV Research and Treatment (5 papers), Ubiquitin and proteasome pathways (4 papers), Malaria Research and Control (4 papers), RNA and protein synthesis mechanisms (4 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Aging (54 citations), Infectious Diseases (229 citations), Virology (28 citations), Public Health, Environmental and Occupational Health (146 citations) and Molecular Biology (380 citations). Prateek Kumar has collaborated with scholars based in India, United States and Russia. Frequent co-authors include Rajanish Giri, Kundlik Gadhave, Neha Garg, Taniya Bhardwaj, Vladimir N. Uversky, Ankur Kumar, Amit Kumar, Carsten Hoege, Anthony A. Hyman and Anne Schwager. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Virology, Journal of Biological Chemistry, Cellular and Molecular Life Sciences and Nature Communications.

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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