Pritish Kumar Varadwaj

3.1k total citations
112 papers, 2.1k citations indexed

About

Pritish Kumar Varadwaj is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Pritish Kumar Varadwaj has authored 112 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Molecular Biology, 20 papers in Computational Theory and Mathematics and 19 papers in Oncology. Recurrent topics in Pritish Kumar Varadwaj's work include Computational Drug Discovery Methods (20 papers), Advanced Chemical Sensor Technologies (11 papers) and Olfactory and Sensory Function Studies (10 papers). Pritish Kumar Varadwaj is often cited by papers focused on Computational Drug Discovery Methods (20 papers), Advanced Chemical Sensor Technologies (11 papers) and Olfactory and Sensory Function Studies (10 papers). Pritish Kumar Varadwaj collaborates with scholars based in India, United States and United Arab Emirates. Pritish Kumar Varadwaj's co-authors include Utkarsh Raj, Imlimaong Aier, Anju Sharma, Rajnish Kumar, Saurabh Gupta, Rahul Semwal, Himansu Kumar, Rashmi Tripathi, Vishal Singh and Pankaj Tyagi and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Bioresource Technology.

In The Last Decade

Pritish Kumar Varadwaj

106 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pritish Kumar Varadwaj India 25 903 345 337 278 179 112 2.1k
Shuguang Yuan China 31 2.6k 2.9× 307 0.9× 690 2.0× 243 0.9× 135 0.8× 85 4.1k
Xuan-Yu Meng China 19 1.5k 1.7× 213 0.6× 906 2.7× 232 0.8× 169 0.9× 48 3.3k
Sun Choi South Korea 29 2.0k 2.2× 126 0.4× 633 1.9× 273 1.0× 142 0.8× 120 3.5k
Cheng Zhao United States 22 1.2k 1.4× 499 1.4× 256 0.8× 80 0.3× 262 1.5× 48 2.0k
Francesca Mancini Italy 37 1.4k 1.5× 130 0.4× 653 1.9× 132 0.5× 232 1.3× 121 4.0k
Upadhyayula Suryanarayana Murty India 25 666 0.7× 267 0.8× 188 0.6× 329 1.2× 297 1.7× 111 2.3k
SubbaRao V. Madhunapantula India 33 1.9k 2.1× 317 0.9× 183 0.5× 233 0.8× 149 0.8× 142 4.1k
Christopher P. Landowski United States 29 1.1k 1.3× 147 0.4× 71 0.2× 275 1.0× 221 1.2× 44 2.6k
Rajnish Kumar India 24 490 0.5× 58 0.2× 229 0.7× 289 1.0× 106 0.6× 116 1.6k
Luciana Scotti Brazil 33 1.3k 1.5× 590 1.7× 645 1.9× 105 0.4× 146 0.8× 283 3.8k

Countries citing papers authored by Pritish Kumar Varadwaj

Since Specialization
Citations

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

Fields of papers citing papers by Pritish Kumar Varadwaj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pritish Kumar Varadwaj

This figure shows the co-authorship network connecting the top 25 collaborators of Pritish Kumar Varadwaj. A scholar is included among the top collaborators of Pritish Kumar Varadwaj 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 Pritish Kumar Varadwaj. Pritish Kumar Varadwaj 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
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Biswas, D.R., Jagat C. Borah, Pritish Kumar Varadwaj, et al.. (2023). Phytochemical mediated modulation of COX-3 and NFκB for the management and treatment of arthritis. Scientific Reports. 13(1). 13612–13612. 5 indexed citations
4.
Sharma, Anju, Rajnish Kumar, & Pritish Kumar Varadwaj. (2023). Smelling the Disease: Diagnostic Potential of Breath Analysis. Molecular Diagnosis & Therapy. 27(3). 321–347. 79 indexed citations
5.
Singh, A. L., et al.. (2023). Anti-inflammatory effect of curcumin in an accelerated senescence model of Wistar rat: an in vivo and in-silico study. Journal of Biomolecular Structure and Dynamics. 43(3). 1459–1470. 4 indexed citations
6.
Semwal, Rahul, Imlimaong Aier, Pankaj Tyagi, Utkarsh Raj, & Pritish Kumar Varadwaj. (2023). DeepLBS: A deep Convolutional Neural Network-Based Ligand-Binding Site Prediction Tool. 1–4. 1 indexed citations
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Singh, Vishal, et al.. (2023). In Silico Study of a Small Bioactive Molecule Targeting Topoisomerase II and P53-MDM2 Complex in Triple-Negative Breast Cancer. ACS Omega. 8(41). 38025–38037. 4 indexed citations
9.
Sharma, Anju, Rajnish Kumar, & Pritish Kumar Varadwaj. (2022). Decoding Seven Basic Odors by Investigating Pharmacophores and MolecularFeatures of Odorants. Current Bioinformatics. 17(8). 759–774. 2 indexed citations
10.
Aier, Imlimaong, et al.. (2022). PGC1 alpha coactivates ERG fusion to drive antioxidant target genes under metabolic stress. Communications Biology. 5(1). 416–416. 6 indexed citations
11.
Singh, Amit Kumar, Harvesh Kumar Rana, Vishal Singh, et al.. (2021). Evaluation of antidiabetic activity of dietary phenolic compound chlorogenic acid in streptozotocin induced diabetic rats: Molecular docking, molecular dynamics, in silico toxicity, in vitro and in vivo studies. Computers in Biology and Medicine. 134. 104462–104462. 67 indexed citations
12.
Sharma, Anju, et al.. (2021). SMILES to Smell: Decoding the Structure–Odor Relationship of Chemical Compounds Using the Deep Neural Network Approach. Journal of Chemical Information and Modeling. 61(2). 676–688. 79 indexed citations
13.
Banerjee, Rudra, et al.. (2021). A study of the COVID‐19 epidemic in India using the SEIRD model. Quantitative Biology. 9(3). 317–328. 1 indexed citations
14.
Sharma, Anju, Rajnish Kumar, Rahul Semwal, et al.. (2020). DeepOlf: Deep Neural Network Based Architecture for Predicting Odorants and Their Interacting Olfactory Receptors. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(1). 418–428. 25 indexed citations
15.
Chaudhary, Amit, Vishal Singh, Pritish Kumar Varadwaj, & Ashutosh Mani. (2020). Screening natural inhibitors against upregulated G-protein coupled receptors as potential therapeutics of Alzheimer’s disease. Journal of Biomolecular Structure and Dynamics. 40(2). 673–684. 4 indexed citations
16.
Raj, Utkarsh, et al.. (2018). Systems Biology: A Powerful Tool for Drug Development. Current Topics in Medicinal Chemistry. 18(20). 1745–1754. 10 indexed citations
17.
Mishra, Sonali, Imlimaong Aier, Pritish Kumar Varadwaj, & Krishna Misra. (2018). Integrated Pathways of Candida albicans Revealing Potential Targets and Key Factors Accountable for Pathogenicity. Proceedings of the National Academy of Sciences India Section B Biological Sciences. 89(2). 575–584. 3 indexed citations
18.
Aier, Imlimaong, Rahul Semwal, Anju Sharma, & Pritish Kumar Varadwaj. (2018). A systematic assessment of statistics, risk factors, and underlying features involved in pancreatic cancer. Cancer Epidemiology. 58. 104–110. 95 indexed citations
19.
Varadwaj, Pritish Kumar, Krishna Misra, Anju Sharma, & Rajnish Kumar. (2010). Mitoxantrone: an agent with promises for anticancer therapies. Electronic journal of biology. 6(2). 12 indexed citations
20.
Varadwaj, Pritish Kumar, et al.. (2009). Functional group based Ligand binding affinity scoring function at atomic environmental level. Bioinformation. 3(6). 268–274. 4 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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