Swarnendu Tripathi

589 total citations
22 papers, 292 citations indexed

About

Swarnendu Tripathi is a scholar working on Molecular Biology, Materials Chemistry and Oncology. According to data from OpenAlex, Swarnendu Tripathi has authored 22 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 8 papers in Materials Chemistry and 3 papers in Oncology. Recurrent topics in Swarnendu Tripathi's work include Protein Structure and Dynamics (10 papers), Enzyme Structure and Function (8 papers) and Genomics and Rare Diseases (3 papers). Swarnendu Tripathi is often cited by papers focused on Protein Structure and Dynamics (10 papers), Enzyme Structure and Function (8 papers) and Genomics and Rare Diseases (3 papers). Swarnendu Tripathi collaborates with scholars based in United States, United Arab Emirates and Canada. Swarnendu Tripathi's co-authors include John J. Portman, Margaret S. Cheung, Pengzhi Zhang, Angel E. Garcı́a, M. Neal Waxham, George I. Makhatadze, Qian Wang, Michael T. Zimmermann, Dirar Homouz and Rathindra N. Bose and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.

In The Last Decade

Swarnendu Tripathi

19 papers receiving 289 citations

Peers

Swarnendu Tripathi
Brian Jo United States
Ioana M. Ilie Netherlands
Thomas Lenz Germany
Lasse Staby Denmark
Jackwee Lim Singapore
Joachim Lätzer United States
Güngör Özer United States
Swarnendu Tripathi
Citations per year, relative to Swarnendu Tripathi Swarnendu Tripathi (= 1×) peers Ilona Christy Unarta

Countries citing papers authored by Swarnendu Tripathi

Since Specialization
Citations

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

Fields of papers citing papers by Swarnendu Tripathi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swarnendu Tripathi

This figure shows the co-authorship network connecting the top 25 collaborators of Swarnendu Tripathi. A scholar is included among the top collaborators of Swarnendu Tripathi 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 Swarnendu Tripathi. Swarnendu Tripathi 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.
Tripathi, Swarnendu, David W. Baggett, Aaron H. Phillips, et al.. (2025). Proteome-wide computational analyses reveal links between protein condensate formation and RNA biology. Science Advances. 11(49). eady1420–eady1420.
2.
Chandra, Bappaditya, Swarnendu Tripathi, & Richard W. Kriwacki. (2024). Properties governing small-molecule partitioning into biomolecular condensates. Nature Chemistry. 16(11). 1743–1745.
3.
Baggett, David W., Anna Medyukhina, Swarnendu Tripathi, et al.. (2022). An Image Analysis Pipeline for Quantifying the Features of Fluorescently-Labeled Biomolecular Condensates in Cells. SHILAP Revista de lepidopterología. 2. 897238–897238. 8 indexed citations
4.
Chi, Young‐In, Timothy J. Stodola, Thiago M. de Assuncao, et al.. (2021). Molecular mechanics and dynamic simulations of well-known Kabuki syndrome-associated KDM6A variants reveal putative mechanisms of dysfunction. Orphanet Journal of Rare Diseases. 16(1). 247–247. 10 indexed citations
5.
Tripathi, Swarnendu, et al.. (2021). Enhanced interpretation of 935 hotspot and non-hotspot RAS variants using evidence-based structural bioinformatics. Computational and Structural Biotechnology Journal. 20. 117–127. 2 indexed citations
6.
Stodola, Timothy J., Young‐In Chi, Thiago M. de Assuncao, et al.. (2021). Computational modeling reveals key molecular properties and dynamic behavior of disruptor of telomeric silencing 1‐like ( DOT1L ) and partnering complexes involved in leukemogenesis. Proteins Structure Function and Bioinformatics. 90(1). 282–298. 4 indexed citations
7.
Čierny, Marek, et al.. (2020). Novel destabilizing Dynactin variant (DCTN1 p.Tyr78His) in patient with Perry syndrome. Parkinsonism & Related Disorders. 77. 110–113. 10 indexed citations
9.
Zhang, Pengzhi, et al.. (2017). Opposing Intermolecular Tuning of Ca2+ Affinity for Calmodulin by Neurogranin and CaMKII Peptides. Biophysical Journal. 112(6). 1105–1119. 10 indexed citations
10.
Tripathi, Swarnendu, Louiza Belkacemi, Margaret S. Cheung, & Rathindra N. Bose. (2016). Correlation between Gene Variants, Signaling Pathways, and Efficacy of Chemotherapy Drugs against Colon Cancers. Cancer Informatics. 15. CIN.S34506–CIN.S34506. 8 indexed citations
11.
Tripathi, Swarnendu, et al.. (2015). Lessons in Protein Design from Combined Evolution and Conformational Dynamics. Scientific Reports. 5(1). 14259–14259. 12 indexed citations
12.
Tripathi, Swarnendu, Louiza Belkacemi, Margaret S. Cheung, & Rathindra N. Bose. (2015). Abstract B1-02: Correlation between oncogenic mutations, signaling pathways, and efficacy of platinum-based drugs against colorectal cancers. Cancer Research. 75(22_Supplement_2). B1–2.
13.
Tripathi, Swarnendu, et al.. (2015). Conformational frustration in calmodulin–target recognition. Journal of Molecular Recognition. 28(2). 74–86. 18 indexed citations
14.
Bose, Rathindra N., Shadi Moghaddas, Louiza Belkacemi, et al.. (2015). Absence of Activation of DNA Repair Genes and Excellent Efficacy of Phosphaplatins against Human Ovarian Cancers: Implications To Treat Resistant Cancers. Journal of Medicinal Chemistry. 58(21). 8387–8401. 20 indexed citations
15.
Tripathi, Swarnendu, Angel E. Garcı́a, & George I. Makhatadze. (2015). Alterations of Nonconserved Residues Affect Protein Stability and Folding Dynamics through Charge–Charge Interactions. The Journal of Physical Chemistry B. 119(41). 13103–13112. 23 indexed citations
16.
Wang, Qian, Pengzhi Zhang, Swarnendu Tripathi, et al.. (2013). Protein recognition and selection through conformational and mutually induced fit. Proceedings of the National Academy of Sciences. 110(51). 20545–20550. 42 indexed citations
17.
Tripathi, Swarnendu & John J. Portman. (2013). Allostery and Folding of the N-terminal Receiver Domain of Protein NtrC. The Journal of Physical Chemistry B. 117(42). 13182–13193. 6 indexed citations
18.
Tripathi, Swarnendu, George I. Makhatadze, & Angel E. Garcı́a. (2012). Backtracking due to Residual Structure in the Unfolded State Changes the Folding of the Third Fibronectin Type III Domain from Tenascin-C. The Journal of Physical Chemistry B. 117(3). 800–810. 11 indexed citations
19.
Tripathi, Swarnendu & John J. Portman. (2009). Inherent flexibility determines the transition mechanisms of the EF-hands of calmodulin. Proceedings of the National Academy of Sciences. 106(7). 2104–2109. 59 indexed citations
20.
Tripathi, Swarnendu & John J. Portman. (2008). Inherent flexibility and protein function: The open/closed conformational transition in the N-terminal domain of calmodulin. The Journal of Chemical Physics. 128(20). 205104–205104. 22 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026