Aditya K. Padhi

1.5k total citations
55 papers, 983 citations indexed

About

Aditya K. Padhi is a scholar working on Molecular Biology, Infectious Diseases and Neurology. According to data from OpenAlex, Aditya K. Padhi has authored 55 papers receiving a total of 983 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 20 papers in Infectious Diseases and 12 papers in Neurology. Recurrent topics in Aditya K. Padhi's work include SARS-CoV-2 and COVID-19 Research (19 papers), vaccines and immunoinformatics approaches (15 papers) and Amyotrophic Lateral Sclerosis Research (12 papers). Aditya K. Padhi is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (19 papers), vaccines and immunoinformatics approaches (15 papers) and Amyotrophic Lateral Sclerosis Research (12 papers). Aditya K. Padhi collaborates with scholars based in India, Japan and Saudi Arabia. Aditya K. Padhi's co-authors include Timir Tripathi, Parismita Kalita, Kam Y. J. Zhang, James Gomes, B. Jayaram, Prakash Saudagar, Rohit Shukla, Suhas Vasaikar, James Gomes and Harish Shukla and has published in prestigious journals such as Journal of the American Chemical Society, Nature Immunology and PLoS ONE.

In The Last Decade

Aditya K. Padhi

48 papers receiving 971 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aditya K. Padhi India 18 571 437 156 126 122 55 983
Dhaval N. Gosalia United States 6 383 0.7× 600 1.4× 73 0.5× 110 0.9× 78 0.6× 7 1.2k
Kornelia Hardes Germany 15 401 0.7× 707 1.6× 95 0.6× 205 1.6× 38 0.3× 39 1.3k
Javier A. Jaimes United States 14 372 0.7× 1.5k 3.4× 150 1.0× 140 1.1× 64 0.5× 21 1.8k
Jinkui Niu United States 10 424 0.7× 646 1.5× 75 0.5× 151 1.2× 133 1.1× 12 1.2k
Lucas Farnung Germany 20 2.0k 3.6× 757 1.7× 174 1.1× 160 1.3× 20 0.2× 30 2.8k
Prakasha Kempaiah United States 18 271 0.5× 257 0.6× 185 1.2× 191 1.5× 23 0.2× 63 1.2k
Jana Schmitzová Germany 18 1.2k 2.0× 678 1.6× 149 1.0× 98 0.8× 10 0.1× 24 2.2k
Sajib Chakraborty Bangladesh 16 525 0.9× 102 0.2× 54 0.3× 90 0.7× 83 0.7× 60 992
Marco R. Straus United States 13 568 1.0× 550 1.3× 53 0.3× 114 0.9× 20 0.2× 18 1.4k
Fikadu Tafesse United States 23 1.2k 2.0× 665 1.5× 20 0.1× 292 2.3× 72 0.6× 57 2.1k

Countries citing papers authored by Aditya K. Padhi

Since Specialization
Citations

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

Fields of papers citing papers by Aditya K. Padhi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aditya K. Padhi. 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 Aditya K. Padhi. The network helps show where Aditya K. Padhi may publish in the future.

Co-authorship network of co-authors of Aditya K. Padhi

This figure shows the co-authorship network connecting the top 25 collaborators of Aditya K. Padhi. A scholar is included among the top collaborators of Aditya K. Padhi 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 Aditya K. Padhi. Aditya K. Padhi 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.
Parmar, Avanish Singh, et al.. (2025). An injectable hydrogel containing N -acetylglycine for the treatment of Gaucher disease. RSC Advances. 15(48). 41220–41240.
2.
Tripathi, Timir, et al.. (2025). An integrated multiscale computational framework deciphers SARS-CoV-2 resistance to sotrovimab. Biophysical Journal. 125(2). 354–376.
3.
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Ojha, Rupal, et al.. (2023). Multi-pathogen based chimeric vaccine to fight against COVID-19 and concomitant coinfections. Biotechnology Letters. 45(7). 779–797. 7 indexed citations
5.
Kalita, Parismita, Timir Tripathi, & Aditya K. Padhi. (2023). Computational Protein Design for COVID-19 Research and Emerging Therapeutics. ACS Central Science. 9(4). 602–613. 12 indexed citations
6.
Padhi, Aditya K., et al.. (2023). From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics. The Journal of Physical Chemistry B. 127(41). 8717–8735. 4 indexed citations
7.
Shukla, Harish, et al.. (2023). Comprehensive analysis of liquid–liquid phase separation propensities of HSV‐1 proteins and their interaction with host factors. Journal of Cellular Biochemistry. 125(12). e30480–e30480. 3 indexed citations
8.
Kalita, Parismita, et al.. (2023). Functional expression, localization, and biochemical characterization of thioredoxin glutathione reductase from air-breathing magur catfish, Clarias magur. International Journal of Biological Macromolecules. 230. 123126–123126. 2 indexed citations
9.
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11.
Padhi, Aditya K. & Timir Tripathi. (2022). A comprehensive protein design protocol to identify resistance mutations and signatures of adaptation in pathogens. Briefings in Functional Genomics. 22(2). 195–203. 12 indexed citations
12.
Padhi, Aditya K. & Timir Tripathi. (2022). Hotspot residues and resistance mutations in the nirmatrelvir-binding site of SARS-CoV-2 main protease: Design, identification, and correlation with globally circulating viral genomes. Biochemical and Biophysical Research Communications. 629. 54–60. 25 indexed citations
13.
Tripathi, Timir, et al.. (2022). Computational Approaches for Development of Engineered Therapeutics against SARS-CoV-2. Biochemistry. 62(3). 669–671. 2 indexed citations
14.
Padhi, Aditya K. & Timir Tripathi. (2022). High-throughput design of symmetrical dimeric SARS-CoV-2 main protease: structural and physical insights into hotspots for adaptation and therapeutics. Physical Chemistry Chemical Physics. 24(16). 9141–9145. 6 indexed citations
15.
Padhi, Aditya K., Jagneshwar Dandapat, Prakash Saudagar, Vladimir N. Uversky, & Timir Tripathi. (2021). Interface‐based design of the favipiravir‐binding site in SARS‐CoV‐2 RNA‐dependent RNA polymerase reveals mutations conferring resistance to chain termination. FEBS Letters. 595(18). 2366–2382. 27 indexed citations
16.
Padhi, Aditya K., et al.. (2021). Accelerating COVID-19 Research Using Molecular Dynamics Simulation. The Journal of Physical Chemistry B. 125(32). 9078–9091. 48 indexed citations
17.
Padhi, Aditya K. & Timir Tripathi. (2021). Targeted design of drug binding sites in the main protease of SARS-CoV-2 reveals potential signatures of adaptation. Biochemical and Biophysical Research Communications. 555. 147–153. 24 indexed citations
18.
Yamashita, Motoi, Hye Sun Kuehn, Kazuki Okuyama, et al.. (2021). A variant in human AIOLOS impairs adaptive immunity by interfering with IKAROS. Nature Immunology. 22(7). 893–903. 40 indexed citations
19.
Padhi, Aditya K., Rohit Shukla, Prakash Saudagar, & Timir Tripathi. (2020). High-throughput rational design of the remdesivir binding site in the RdRp of SARS-CoV-2: implications for potential resistance. iScience. 24(1). 101992–101992. 64 indexed citations
20.
Padhi, Aditya K. & Timir Tripathi. (2020). Can SARS-CoV-2 Accumulate Mutations in the S-Protein to Increase Pathogenicity?. ACS Pharmacology & Translational Science. 3(5). 1023–1026. 57 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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