Sanjib Senapati

3.0k total citations
105 papers, 2.6k citations indexed

About

Sanjib Senapati is a scholar working on Molecular Biology, Organic Chemistry and Catalysis. According to data from OpenAlex, Sanjib Senapati has authored 105 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 26 papers in Organic Chemistry and 22 papers in Catalysis. Recurrent topics in Sanjib Senapati's work include Surfactants and Colloidal Systems (21 papers), Ionic liquids properties and applications (21 papers) and Spectroscopy and Quantum Chemical Studies (16 papers). Sanjib Senapati is often cited by papers focused on Surfactants and Colloidal Systems (21 papers), Ionic liquids properties and applications (21 papers) and Spectroscopy and Quantum Chemical Studies (16 papers). Sanjib Senapati collaborates with scholars based in India, United States and Hong Kong. Sanjib Senapati's co-authors include Amalendu Chandra, Max L. Berkowitz, Debostuti Ghoshdastidar, Aneesh Chandran, Venkat R. Chirasani, Ramesh L. Gardas, Malcolm D. E. Forbes, Mohd Ahsan, L. Perera and Kathiresan Natarajan and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and Nucleic Acids Research.

In The Last Decade

Sanjib Senapati

103 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sanjib Senapati India 29 709 627 566 516 493 105 2.6k
Orlando Acevedo United States 28 744 1.0× 881 1.4× 478 0.8× 456 0.9× 1.0k 2.1× 90 3.4k
Seishi Shimizu United Kingdom 36 1.2k 1.6× 621 1.0× 857 1.5× 900 1.7× 531 1.1× 117 3.8k
Bernd Ensing Netherlands 39 1.2k 1.7× 729 1.2× 1.1k 2.0× 533 1.0× 331 0.7× 86 4.1k
Paul J. van Maaren Sweden 15 827 1.2× 387 0.6× 1.3k 2.4× 650 1.3× 177 0.4× 20 3.0k
Chengbu Liu China 32 474 0.7× 1.4k 2.2× 678 1.2× 566 1.1× 489 1.0× 268 4.3k
Sandip Paul India 31 1.0k 1.4× 289 0.5× 604 1.1× 332 0.6× 433 0.9× 122 2.5k
Yoshikata Koga Canada 34 271 0.4× 882 1.4× 1.1k 2.0× 1.3k 2.5× 737 1.5× 155 3.6k
Feng Wang Australia 33 693 1.0× 759 1.2× 1.1k 1.9× 382 0.7× 392 0.8× 234 3.9k
Éric Hénon France 17 337 0.5× 1.1k 1.8× 442 0.8× 327 0.6× 281 0.6× 55 3.5k
Munir S. Skaf Brazil 41 1.4k 2.0× 415 0.7× 1.2k 2.1× 1.4k 2.7× 191 0.4× 139 4.9k

Countries citing papers authored by Sanjib Senapati

Since Specialization
Citations

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

Fields of papers citing papers by Sanjib Senapati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sanjib Senapati

This figure shows the co-authorship network connecting the top 25 collaborators of Sanjib Senapati. A scholar is included among the top collaborators of Sanjib Senapati 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 Sanjib Senapati. Sanjib Senapati 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.
Senapati, Sanjib, et al.. (2023). Comprehending the Structure, Dynamics, and Mechanism of Action of Drug-Resistant HIV Protease. ACS Omega. 8(11). 9748–9763. 8 indexed citations
2.
Kumar, Shailesh, Atul Kumar Singh, Prem Prakash Kushwaha, et al.. (2021). Identification of Compounds from Curcuma longa with In Silico Binding Potential against SARS-CoV-2 and Human Host Proteins Involve in Virus Entry and Pathogenesis. Indian Journal of Pharmaceutical Sciences. 83(6). 8 indexed citations
3.
4.
Mondal, Barun, et al.. (2020). “Novel Dextrin‐Cysteine Schiff Base: A Highly Efficient Sensor for Mercury Ions in Aqueous Environment”. ChemistrySelect. 5(6). 2082–2093. 14 indexed citations
5.
Ahsan, Mohd, et al.. (2019). Steering the Lipid Transfer To Unravel the Mechanism of Cholesteryl Ester Transfer Protein Inhibition. Biochemistry. 58(36). 3789–3801. 14 indexed citations
6.
Bose, A., P. Sengupta, Uttam Pal, et al.. (2018). Encapsulation of Thymol in cyclodextrin nano-cavities: A multi spectroscopic and theoretical study. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 208. 339–348. 22 indexed citations
7.
8.
Gardas, Ramesh L., et al.. (2017). How water manifests the structural regimes in ionic liquids. Soft Matter. 13(12). 2348–2361. 18 indexed citations
9.
Durairajan, Siva Sundara Kumar, Yingyu Huang, Leilei Chen, et al.. (2014). Effects of Huanglian-Jie-Du-Tang and Its Modified Formula on the Modulation of Amyloid-β Precursor Protein Processing in Alzheimer's Disease Models. PLoS ONE. 9(3). e92954–e92954. 32 indexed citations
10.
Chirasani, Venkat R., Dhiman Ghosh, Amal Kanti Bera, et al.. (2013). Naturally Occurring Variants of the Dysglycemic Peptide Pancreastatin. Journal of Biological Chemistry. 289(7). 4455–4469. 15 indexed citations
11.
12.
Natarajan, Kathiresan & Sanjib Senapati. (2012). Understanding the Basis of Drug Resistance of the Mutants of αβ-Tubulin Dimer via Molecular Dynamics Simulations. PLoS ONE. 7(8). e42351–e42351. 36 indexed citations
13.
Senapati, Sanjib, et al.. (2011). Dynamic flaps in HIV‐1 protease adopt unique ordering at different stages in the catalytic cycle. Proteins Structure Function and Bioinformatics. 79(6). 1830–1840. 29 indexed citations
14.
Chandran, Aneesh, et al.. (2010). Structure and dynamics of acetate anion-based ionic liquids from molecular dynamics study. Chemical Physics. 374(1-3). 46–54. 37 indexed citations
15.
Senapati, Sanjib & Max L. Berkowitz. (2003). Water structure and dynamics in phosphate fluorosurfactant based reverse micelle: A computer simulation study. The Journal of Chemical Physics. 118(4). 1937–1944. 79 indexed citations
16.
Senapati, Sanjib, Jason S. Keiper, Joseph M. DeSimone, et al.. (2002). Structure of Phosphate Fluorosurfactant Based Reverse Micelles in Supercritical Carbon Dioxide. Langmuir. 18(20). 7371–7376. 76 indexed citations
17.
Senapati, Sanjib. (2002). A molecular dynamics simulation study of the dimethyl sulfoxide liquid–vapor interface. The Journal of Chemical Physics. 117(4). 1812–1816. 30 indexed citations
18.
Senapati, Sanjib & Max L. Berkowitz. (2001). Computer Simulation Study of the Interface Width of the Liquid/Liquid Interface. Physical Review Letters. 87(17). 176101–176101. 130 indexed citations
19.
Senapati, Sanjib & Amalendu Chandra. (2000). Structure of a mixed dipolar liquid near a metal surface: A combined approach of weighted density and perturbative approximations. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 62(1). 1017–1024. 4 indexed citations
20.
Chandra, Amalendu, et al.. (1998). Dynamics of polarization relaxation at solid–liquid interface. The Journal of Chemical Physics. 109(23). 10439–10445. 8 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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