Prateek Kumar

1.5k total citations
65 papers, 862 citations indexed

About

Prateek Kumar is a scholar working on Molecular Biology, Infectious Diseases and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Prateek Kumar has authored 65 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 20 papers in Infectious Diseases and 19 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Prateek Kumar's work include Mosquito-borne diseases and control (17 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Computational Drug Discovery Methods (10 papers). Prateek Kumar is often cited by papers focused on Mosquito-borne diseases and control (17 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Computational Drug Discovery Methods (10 papers). Prateek Kumar collaborates with scholars based in India, United States and Russia. Prateek Kumar's co-authors include Rajanish Giri, Kundlik Gadhave, Neha Garg, Taniya Bhardwaj, Vladimir N. Uversky, Amit Kumar, Ankur Kumar, Deepak Kumar, Anne Schwager and Carsten Hoege and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Prateek Kumar

62 papers receiving 849 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Prateek Kumar India 19 421 278 167 84 76 65 862
Jan Šilhán Czechia 15 869 2.1× 319 1.1× 40 0.2× 81 1.0× 80 1.1× 29 1.2k
Md. Zubbair Malik India 19 523 1.2× 172 0.6× 103 0.6× 71 0.8× 152 2.0× 89 928
Jonathan Cechetto South Korea 16 536 1.3× 198 0.7× 203 1.2× 232 2.8× 165 2.2× 25 1.1k
André S. Godoy Brazil 16 294 0.7× 242 0.9× 161 1.0× 41 0.5× 155 2.0× 38 672
Xavier C. Ding Switzerland 24 552 1.3× 144 0.5× 807 4.8× 115 1.4× 172 2.3× 48 1.6k
Ashok Kumar Patel India 17 573 1.4× 123 0.4× 111 0.7× 37 0.4× 52 0.7× 47 861
Aditi Singh India 20 787 1.9× 273 1.0× 56 0.3× 296 3.5× 146 1.9× 86 1.3k
J. Brandão-Neto United Kingdom 18 729 1.7× 112 0.4× 43 0.3× 54 0.6× 125 1.6× 55 1.1k
Ákos Putics Hungary 13 396 0.9× 834 3.0× 63 0.4× 64 0.8× 189 2.5× 15 1.4k
Samiul Hasan United Kingdom 10 511 1.2× 256 0.9× 456 2.7× 171 2.0× 347 4.6× 20 1.1k

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-authorship network of co-authors of Prateek Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Prateek Kumar. A scholar is included among the top collaborators of Prateek Kumar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Prateek Kumar. Prateek Kumar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kumar, Prateek, et al.. (2025). Signal Peptide of Human Serum Albumin (residues 1–18) Forms Amyloid-like Aggregates. ACS Omega. 10(30). 32673–32679. 1 indexed citations
2.
Kumar, Prateek, et al.. (2023). Correlation between value of Hba1c and degree of sensorineural hearing loss in type 2 diabetics. International Journal of Research in Medical Sciences. 11(7). 2605–2610.
3.
Kumar, Prateek, et al.. (2023). Coronaviruses spike glycoprotein endodomains: The sequence and structure‐based comprehensive study. Protein Science. 32(11). e4804–e4804. 2 indexed citations
4.
Singh, Sanjeev Kumar, et al.. (2023). Land Registration System using Blockchain. 1499–1503. 2 indexed citations
5.
Bhardwaj, Taniya, Kundlik Gadhave, Prateek Kumar, et al.. (2023). Amyloidogenic proteins in the SARS-CoV and SARS-CoV-2 proteomes. Nature Communications. 14(1). 945–945. 25 indexed citations
6.
Kumar, Prateek, et al.. (2023). Investigating the aggregation perspective of Dengue virus proteome. Virology. 586. 12–22. 1 indexed citations
7.
Sharma, Nitin, Kundlik Gadhave, Prateek Kumar, & Rajanish Giri. (2022). Transactivation domain of Adenovirus Early Region 1A (E1A): Investigating folding dynamics and aggregation. SHILAP Revista de lepidopterología. 4. 29–40. 3 indexed citations
8.
Kumar, Prateek, et al.. (2022). Role of structural disorder in the multi-functionality of flavivirus proteins. Expert Review of Proteomics. 19(3). 183–196. 2 indexed citations
9.
10.
Bhardwaj, Taniya, Prateek Kumar, & Rajanish Giri. (2022). Investigating the conformational dynamics of Zika virus NS4B protein. Virology. 575. 20–35. 8 indexed citations
11.
Singh, Ashutosh, Ankur Kumar, Prateek Kumar, et al.. (2021). Salvianolic Acid B Noncovalently Interacts With Disordered c-Myc: A Computational and Spectroscopic-Based Study. Future Medicinal Chemistry. 13(16). 1341–1352. 5 indexed citations
12.
Kumar, Amit, et al.. (2021). SARS-CoV-2 NSP1 C-terminal (residues 131–180) is an intrinsically disordered region in isolation. SHILAP Revista de lepidopterología. 2. 100007–100007. 20 indexed citations
13.
Sharma, Nitin, et al.. (2020). Small molecule inhibitors possibly targeting the rearrangement of Zika virus envelope protein. Antiviral Research. 182. 104876–104876. 13 indexed citations
14.
Singh, Ashutosh, Prateek Kumar, Rohit Sharma, et al.. (2020). Quercetin acts as a P-gp modulator via impeding signal transduction from nucleotide-binding domain to transmembrane domain. Journal of Biomolecular Structure and Dynamics. 40(10). 4507–4515. 32 indexed citations
15.
Giri, Rajanish, Taniya Bhardwaj, Prateek Kumar, et al.. (2020). Understanding COVID-19 via comparative analysis of dark proteomes of SARS-CoV-2, human SARS and bat SARS-like coronaviruses. Cellular and Molecular Life Sciences. 78(4). 1655–1688. 85 indexed citations
16.
Sharma, Nitin, Prateek Kumar, & Rajanish Giri. (2020). Polysaccharides like pentagalloylglucose, parishin a and stevioside inhibits the viral entry by binding the Zika virus envelope protein. Journal of Biomolecular Structure and Dynamics. 39(16). 6008–6020. 12 indexed citations
17.
Kumar, Amit, et al.. (2020). Exploring the SARS-CoV-2 structural proteins for multi-epitope vaccine development: an in-silico approach. Expert Review of Vaccines. 19(9). 887–898. 19 indexed citations
18.
Yadav, Rakhi, Chandrabose Selvaraj, Murali Aarthy, et al.. (2020). Investigating into the molecular interactions of flavonoids targeting NS2B-NS3 protease from ZIKA virus through in-silico approaches. Journal of Biomolecular Structure and Dynamics. 39(1). 272–284. 30 indexed citations
19.
Kumar, Deepak, Murali Aarthy, Prateek Kumar, et al.. (2019). Targeting the NTPase site of Zika virus NS3 helicase for inhibitor discovery. Journal of Biomolecular Structure and Dynamics. 38(16). 4827–4837. 10 indexed citations
20.
Kumar, Prateek & Rajanish Giri. (2019). Identification of peptidomimetic compounds as potential inhibitors against MurA enzyme of Mycobacterium tuberculosis. Journal of Biomolecular Structure and Dynamics. 38(17). 4997–5013. 18 indexed citations

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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