Umesh Panwar

630 total citations
20 papers, 408 citations indexed

About

Umesh Panwar is a scholar working on Computational Theory and Mathematics, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Umesh Panwar has authored 20 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Theory and Mathematics, 11 papers in Molecular Biology and 6 papers in Infectious Diseases. Recurrent topics in Umesh Panwar's work include Computational Drug Discovery Methods (14 papers), HIV Research and Treatment (4 papers) and HIV/AIDS drug development and treatment (4 papers). Umesh Panwar is often cited by papers focused on Computational Drug Discovery Methods (14 papers), HIV Research and Treatment (4 papers) and HIV/AIDS drug development and treatment (4 papers). Umesh Panwar collaborates with scholars based in India, Saudi Arabia and Czechia. Umesh Panwar's co-authors include Sanjeev Kumar Singh, Chandrabose Selvaraj, Dhurvas Chandrasekaran Dinesh, Evžen Bouřa, Murali Aarthy, Anuraj Nayarisseri, Poonam C. Singh, Vikash Kumar Dubey, Khushboo Sharma and Tajamul Hussain and has published in prestigious journals such as Scientific Reports, Current Pharmaceutical Design and Applied Biochemistry and Biotechnology.

In The Last Decade

Umesh Panwar

20 papers receiving 406 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Umesh Panwar India 13 216 208 115 65 38 20 408
Lovika Mittal India 12 164 0.8× 214 1.0× 136 1.2× 61 0.9× 12 0.3× 18 388
Mitul Srivastava India 12 195 0.9× 224 1.1× 154 1.3× 62 1.0× 12 0.3× 26 429
Francesca Alessandra Ambrosio Italy 15 360 1.7× 125 0.6× 175 1.5× 120 1.8× 33 0.9× 38 697
Matteo Pavan Italy 14 303 1.4× 171 0.8× 154 1.3× 122 1.9× 14 0.4× 34 537
Sathishkumar Chinnasamy India 11 208 1.0× 147 0.7× 117 1.0× 58 0.9× 10 0.3× 18 400
Mutaib M. Mashraqi Saudi Arabia 12 184 0.9× 90 0.4× 67 0.6× 80 1.2× 11 0.3× 36 364
Amr Alhossary Singapore 5 304 1.4× 269 1.3× 75 0.7× 57 0.9× 8 0.2× 10 533
Salman Ali Khan Pakistan 8 153 0.7× 200 1.0× 207 1.8× 79 1.2× 17 0.4× 24 422
Amar Ajmal Pakistan 10 153 0.7× 110 0.5× 31 0.3× 101 1.6× 15 0.4× 24 325
Abdulrahim A. Alzain Sudan 13 218 1.0× 139 0.7× 65 0.6× 119 1.8× 7 0.2× 66 431

Countries citing papers authored by Umesh Panwar

Since Specialization
Citations

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

Fields of papers citing papers by Umesh Panwar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Umesh Panwar

This figure shows the co-authorship network connecting the top 25 collaborators of Umesh Panwar. A scholar is included among the top collaborators of Umesh Panwar 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 Umesh Panwar. Umesh Panwar 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.
Nayarisseri, Anuraj, Mohnad Abdalla, Khushboo Sharma, et al.. (2024). Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer. Scientific Reports. 14(1). 12 indexed citations
2.
Gupta, Pawan, Umesh Panwar, & Sanjeev Kumar Singh. (2024). Novel scaffolds identification against Mpro of SARS-CoV-2 using shape based screening and molecular simulation methods. Chemical Physics Impact. 8. 100496–100496. 4 indexed citations
3.
Sharma, Khushboo, Umesh Panwar, Shweta Agrawal, et al.. (2023). Unveiling the ESR1 Conformational Stability and Screening PotentInhibitors for Breast Cancer Treatment. Medicinal Chemistry. 20(3). 352–368. 1 indexed citations
4.
Panwar, Umesh, et al.. (2023). Virtual Screening Process: A Guide in Modern Drug Designing. Methods in molecular biology. 2714. 21–31. 2 indexed citations
5.
Abdalla, Mohnad, Umesh Panwar, Sarah Albogami, et al.. (2023). Structure-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation of EGFR for the Clinical Treatment of Glioblastoma. Applied Biochemistry and Biotechnology. 195(8). 5094–5119. 13 indexed citations
6.
Selvaraj, Chandrabose, Umesh Panwar, Ramalingam Karthik Raja, Rajendran Vijayakumar, & Sanjeev Kumar Singh. (2022). Exploring the macromolecules for secretory pathway in cancer disease. Advances in protein chemistry and structural biology. 133. 55–83. 2 indexed citations
7.
8.
Selvaraj, Chandrabose, Umesh Panwar, Dhurvas Chandrasekaran Dinesh, et al.. (2021). Microsecond MD Simulation and Multiple-Conformation Virtual Screening to Identify Potential Anti-COVID-19 Inhibitors Against SARS-CoV-2 Main Protease. Frontiers in Chemistry. 8. 595273–595273. 43 indexed citations
9.
Aarthy, Murali, Umesh Panwar, & Sanjeev Kumar Singh. (2020). Structural dynamic studies on identification of EGCG analogues for the inhibition of Human Papillomavirus E7. Scientific Reports. 10(1). 8661–8661. 15 indexed citations
10.
Nayarisseri, Anuraj, Ravina Khandelwal, Chandrabose Selvaraj, et al.. (2020). Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation. Current Topics in Medicinal Chemistry. 20(24). 2146–2167. 27 indexed citations
11.
Selvaraj, Chandrabose, Dhurvas Chandrasekaran Dinesh, Umesh Panwar, Evžen Bouřa, & Sanjeev Kumar Singh. (2020). High-Throughput Screening and Quantum Mechanics for Identifying Potent Inhibitors Against Mac1 Domain of SARS-CoV-2 Nsp3. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18(4). 1262–1270. 19 indexed citations
12.
Selvaraj, Chandrabose, et al.. (2020). Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19. Journal of Biomolecular Structure and Dynamics. 39(13). 4582–4593. 75 indexed citations
13.
Panwar, Umesh & Sanjeev Kumar Singh. (2020). Atom-based 3D-QSAR, molecular docking, DFT, and simulation studies of acylhydrazone, hydrazine, and diazene derivatives as IN-LEDGF/p75 inhibitors. Structural Chemistry. 32(1). 337–352. 49 indexed citations
14.
Panwar, Umesh, et al.. (2019). An In silico Approach to Identify High Affinity Small Molecule Targeting m-TOR Inhibitors for the Clinical Treatment of Breast Cancer. Asian Pacific Journal of Cancer Prevention. 20(4). 1229–1241. 24 indexed citations
15.
Panwar, Umesh, et al.. (2019). Current Computational Approaches for the Development of Anti-HIV Inhibitors: An Overview. Current Pharmaceutical Design. 25(31). 3390–3405. 11 indexed citations
16.
Suryanarayanan, Venkatesan, et al.. (2018). De Novo Design of Ligands Using Computational Methods. Methods in molecular biology. 1762. 71–86. 5 indexed citations
17.
Panwar, Umesh & Sanjeev Kumar Singh. (2018). An Overview on Zika Virus and the Importance of Computational Drug Discovery. 3(2). 43–51. 11 indexed citations
18.
Panwar, Umesh & Sanjeev Kumar Singh. (2018). Identification of Novel Pancreatic Lipase Inhibitors UsingIn SilicoStudies. Endocrine Metabolic & Immune Disorders - Drug Targets. 19(4). 449–457. 15 indexed citations
19.
Panwar, Umesh & Sanjeev Kumar Singh. (2017). Structure-based virtual screening toward the discovery of novel inhibitors for impeding the protein-protein interaction between HIV-1 integrase and human lens epithelium-derived growth factor (LEDGF/p75). Journal of Biomolecular Structure and Dynamics. 36(12). 3199–3217. 35 indexed citations
20.
Aarthy, Murali, Umesh Panwar, Chandrabose Selvaraj, & Sanjeev Kumar Singh. (2017). Advantages of Structure-Based Drug Design Approaches in Neurological Disorders. Current Neuropharmacology. 15(8). 20 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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