Vinay Kumar

1.4k total citations
57 papers, 1.0k citations indexed

About

Vinay Kumar is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Vinay Kumar has authored 57 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computational Theory and Mathematics, 15 papers in Molecular Biology and 11 papers in Pharmacology. Recurrent topics in Vinay Kumar's work include Computational Drug Discovery Methods (24 papers), Cholinesterase and Neurodegenerative Diseases (9 papers) and Synthesis and biological activity (7 papers). Vinay Kumar is often cited by papers focused on Computational Drug Discovery Methods (24 papers), Cholinesterase and Neurodegenerative Diseases (9 papers) and Synthesis and biological activity (7 papers). Vinay Kumar collaborates with scholars based in India, United States and Czechia. Vinay Kumar's co-authors include Kunal Roy, Probir Kumar Ojha, Achintya Saha, Arkaprava Banerjee, Arindam Talukdar, Biswajit Kundu, Sourav Pal, Priyanka De, Mahesh Mohan and Supratik Kar and has published in prestigious journals such as New England Journal of Medicine, Journal of Biological Chemistry and Environmental Science & Technology.

In The Last Decade

Vinay Kumar

51 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vinay Kumar India 20 384 379 193 155 117 57 1.0k
Sarah Naomi Bolz Germany 8 300 0.8× 757 2.0× 249 1.3× 146 0.9× 75 0.6× 12 1.4k
Shopnil Akash Bangladesh 19 187 0.5× 469 1.2× 165 0.9× 110 0.7× 70 0.6× 91 1.2k
Karthikeyan Muthusamy India 20 340 0.9× 632 1.7× 167 0.9× 134 0.9× 53 0.5× 138 1.4k
Manish Tripathi India 19 358 0.9× 349 0.9× 210 1.1× 357 2.3× 53 0.5× 93 1.4k
Partha Biswas Bangladesh 26 302 0.8× 510 1.3× 97 0.5× 187 1.2× 66 0.6× 90 1.5k
Shailima Rampogu South Korea 20 334 0.9× 524 1.4× 256 1.3× 114 0.7× 50 0.4× 60 1.0k
Chaofeng Lou China 9 559 1.5× 472 1.2× 263 1.4× 117 0.8× 49 0.4× 11 1.2k
Ramakrishna Vadde India 19 191 0.5× 430 1.1× 105 0.5× 105 0.7× 52 0.4× 52 1.1k
Zhenquan Hu China 16 224 0.6× 648 1.7× 256 1.3× 161 1.0× 48 0.4× 33 1.3k
Yunierkis Pérez‐Castillo Ecuador 22 475 1.2× 668 1.8× 297 1.5× 190 1.2× 42 0.4× 84 1.5k

Countries citing papers authored by Vinay Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Vinay Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vinay Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Vinay Kumar. A scholar is included among the top collaborators of Vinay 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 Vinay Kumar. Vinay 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.
Chang, Chia‐Ming, Arkaprava Banerjee, Vinay Kumar, Kunal Roy, & Emilio Benfenati. (2025). The q-RASPR approach for predicting the property and fate of persistent organic pollutants. Scientific Reports. 15(1). 1344–1344. 2 indexed citations
2.
Kumar, Vinay & Kunal Roy. (2024). Protein-protein interaction network analysis for the identification of novel multi-target inhibitors and target miRNAs against Alzheimer’s disease. Advances in protein chemistry and structural biology. 139. 405–467. 3 indexed citations
3.
Kumar, Vinay, Arkaprava Banerjee, & Kunal Roy. (2024). Innovative strategies for the quantitative modeling of blood–brain barrier (BBB) permeability: harnessing the power of machine learning-based q-RASAR approach. Molecular Systems Design & Engineering. 9(7). 729–743. 5 indexed citations
4.
5.
Kumar, Vinay, Arkaprava Banerjee, & Kunal Roy. (2023). Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease. Chemometrics and Intelligent Laboratory Systems. 245. 105049–105049. 18 indexed citations
6.
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8.
Kumar, Vinay, et al.. (2022). Analysis of Indications and outcome of emergency obstetric hysterectomy. International Journal of Clinical Obstetrics and Gynaecology. 6(1). 5–9.
9.
Khan, Kabiruddin, et al.. (2022). Intelligent consensus predictions of bioconcentration factor of pharmaceuticals using 2D and fragment-based descriptors. Environment International. 170. 107625–107625. 20 indexed citations
10.
Banerjee, Arkaprava, Priyanka De, Vinay Kumar, Supratik Kar, & Kunal Roy. (2022). Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across. Chemosphere. 309(Pt 1). 136579–136579. 27 indexed citations
11.
Kumar, Vinay, Ashish Dogra, Probir Kumar Ojha, et al.. (2021). Amalgamation of in-silico, in-vitro and in-vivo approach to establish glabridin as a potential CYP2E1 inhibitor. Xenobiotica. 51(6). 625–635. 15 indexed citations
12.
Kumar, Vinay, et al.. (2021). Chemometric modeling of plant protection products (PPPs) for the prediction of acute contact toxicity against honey bees (A. mellifera): A 2D-QSAR approach. Journal of Hazardous Materials. 423(Pt B). 127230–127230. 24 indexed citations
13.
Kumar, Vinay, et al.. (2020). SOCIAL NETWORKING FOR A LEARNING MANAGEMENT SYSTEM - SHOULD FACEBOOK BE USED TO SUPPLEMENT BLACKBOARD?. Issues in Information Systems. 1 indexed citations
14.
Kumar, Vinay, Probir Kumar Ojha, Achintya Saha, & Kunal Roy. (2020). Cheminformatic modelling of β-amyloid aggregation inhibitory activity against Alzheimer's disease. Computers in Biology and Medicine. 118. 103658–103658. 8 indexed citations
15.
Chakraborty, Samrat, Biswajit Mukherjee, Shila Elizabeth Besra, et al.. (2020). Aptamer-Functionalized Drug Nanocarrier Improves Hepatocellular Carcinoma toward Normal by Targeting Neoplastic Hepatocytes. Molecular Therapy — Nucleic Acids. 20. 34–49. 41 indexed citations
16.
17.
Kumar, Vinay, Achintya Saha, & Kunal Roy. (2020). In silico modeling for dual inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) enzymes in Alzheimer’s disease. Computational Biology and Chemistry. 88. 107355–107355. 42 indexed citations
18.
Jayaraj, Abhilash, Vinay Kumar, Brian S. J. Blagg, et al.. (2019). Stimulation of heat shock protein 90 chaperone function through binding of a novobiocin analog KU-32. Journal of Biological Chemistry. 294(16). 6450–6467. 11 indexed citations
19.
Pandey, A. K., Aman Kumar, Inderjeet Singh, et al.. (2018). Polymorphism of melatonin receptor (MTNR1A) gene and its association with seasonal reproduction in water buffalo (Bubalus bubalis). Animal Reproduction Science. 199. 51–59. 14 indexed citations
20.
Fidock, Mark, Carl Laxton, Peter Colman, et al.. (2011). The Innate Immune Response, Clinical Outcomes, and Ex Vivo HCV Antiviral Efficacy of a TLR7 Agonist (PF-4878691). Clinical Pharmacology & Therapeutics. 89(6). 821–829. 64 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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