Swapnil C. Devarkar

946 total citations
18 papers, 592 citations indexed

About

Swapnil C. Devarkar is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Swapnil C. Devarkar has authored 18 papers receiving a total of 592 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Immunology and 3 papers in Infectious Diseases. Recurrent topics in Swapnil C. Devarkar's work include interferon and immune responses (6 papers), RNA modifications and cancer (3 papers) and Immune Response and Inflammation (3 papers). Swapnil C. Devarkar is often cited by papers focused on interferon and immune responses (6 papers), RNA modifications and cancer (3 papers) and Immune Response and Inflammation (3 papers). Swapnil C. Devarkar collaborates with scholars based in United States, France and Germany. Swapnil C. Devarkar's co-authors include Smita S. Patel, Joseph Marcotrigiano, Abdul Ghafoor Khan, Fuguo Jiang, Matthew T. Miller, Anand Ramanathan, Chen Wang, Yong Xiong, Ivan B. Lomakin and Yingxia Hu and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Swapnil C. Devarkar

16 papers receiving 586 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Swapnil C. Devarkar United States 10 415 256 156 55 52 18 592
Siqi Hu China 13 412 1.0× 238 0.9× 91 0.6× 57 1.0× 73 1.4× 38 653
Parimal Kumar United States 6 306 0.7× 100 0.4× 71 0.5× 91 1.7× 33 0.6× 7 423
Adrijana Stefanovic Austria 4 320 0.8× 439 1.7× 122 0.8× 48 0.9× 61 1.2× 5 667
Line Lykke Andersen Germany 8 188 0.5× 300 1.2× 99 0.6× 22 0.4× 33 0.6× 9 432
Xiaohan Ning China 6 453 1.1× 497 1.9× 149 1.0× 18 0.3× 34 0.7× 9 693
Johannes Schwerk United States 11 184 0.4× 260 1.0× 82 0.5× 40 0.7× 61 1.2× 15 507
Christian Urban Germany 8 176 0.4× 170 0.7× 56 0.4× 25 0.5× 21 0.4× 15 342
JoAnn C. Castelli United States 7 266 0.6× 320 1.3× 68 0.4× 56 1.0× 35 0.7× 9 539
Anna Serquiña United States 6 286 0.7× 96 0.4× 70 0.4× 30 0.5× 179 3.4× 7 457
Ann Brasey Canada 6 278 0.7× 118 0.5× 74 0.5× 89 1.6× 15 0.3× 9 433

Countries citing papers authored by Swapnil C. Devarkar

Since Specialization
Citations

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

Fields of papers citing papers by Swapnil C. Devarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Swapnil C. Devarkar. 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 Swapnil C. Devarkar. The network helps show where Swapnil C. Devarkar may publish in the future.

Co-authorship network of co-authors of Swapnil C. Devarkar

This figure shows the co-authorship network connecting the top 25 collaborators of Swapnil C. Devarkar. A scholar is included among the top collaborators of Swapnil C. Devarkar 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 Swapnil C. Devarkar. Swapnil C. Devarkar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Devarkar, Swapnil C., Yuan Ren, Julien Berro, et al.. (2025). Nodal modulator (NOMO) is a force-bearing transmembrane protein required for muscle differentiation. The Journal of Cell Biology. 224(9).
2.
Zheng, Wei, Jimin Wang, Pengxin Chai, et al.. (2025). Visualizing the translation landscape in human cells at high resolution. Nature Communications. 16(1). 10757–10757.
3.
Wu, Chunxiang, Megan E. Meuser, Swapnil C. Devarkar, et al.. (2025). Distinct Target Site of Lenacapavir in Immature HIV-1 and Concurrent Binding with the Maturation Inhibitor Bevirimat. Journal of the American Chemical Society. 147(46). 42685–42700. 1 indexed citations
4.
Devarkar, Swapnil C., et al.. (2025). Structural basis for aminoacylation of cellular modified tRNALys3 by human lysyl-tRNA synthetase. Nucleic Acids Research. 53(5). 2 indexed citations
5.
Lomakin, Ivan B., Swapnil C. Devarkar, Ayman Grada, & Christopher G. Bunick. (2024). Mechanistic Basis for the Translation Inhibition of Cutibacterium acnes by Clindamycin. Journal of Investigative Dermatology. 144(11). 2553–2561.e3. 2 indexed citations
6.
Lomakin, Ivan B., et al.. (2024). Practical Guide for Implementing Cryogenic Electron Microscopy Structure Determination in Dermatology Research. Journal of Investigative Dermatology. 145(1). 22–31. 1 indexed citations
7.
Lomakin, Ivan B., et al.. (2023). Sarecycline inhibits protein translation inCutibacterium acnes70S ribosome using a two-site mechanism. Nucleic Acids Research. 51(6). 2915–2930. 11 indexed citations
8.
Devarkar, Swapnil C., et al.. (2023). RIG-I recognizes metabolite-capped RNAs as signaling ligands. Nucleic Acids Research. 51(15). 8102–8114. 15 indexed citations
9.
Devarkar, Swapnil C., Ivan B. Lomakin, Luojia Yang, et al.. (2023). Structural basis for translation inhibition by MERS-CoV Nsp1 reveals a conserved mechanism for betacoronaviruses. Cell Reports. 42(10). 113156–113156. 7 indexed citations
10.
Chai, Pengxin, et al.. (2022). Structures of a mobile intron retroelement poised to attack its structured DNA target. Science. 378(6620). 627–634. 17 indexed citations
11.
Devarkar, Swapnil C., Jie Zheng, Bruce D. Pascal, et al.. (2022). The intrinsically disordered CARDs‐Helicase linker in RIG‐I is a molecular gate for RNA proofreading. The EMBO Journal. 41(10). e109782–e109782. 13 indexed citations
12.
Cameron, Christopher J. F., et al.. (2021). Nodal modulator (NOMO) is required to sustain endoplasmic reticulum morphology. Journal of Biological Chemistry. 297(2). 100937–100937. 9 indexed citations
13.
Yuan, Shuai, Lei Peng, Jonathan J. Park, et al.. (2020). Nonstructural Protein 1 of SARS-CoV-2 Is a Potent Pathogenicity Factor Redirecting Host Protein Synthesis Machinery toward Viral RNA. Molecular Cell. 80(6). 1055–1066.e6. 134 indexed citations
14.
Hu, Yingxia, et al.. (2019). APOBEC3A Loop 1 Is a Determinant for Single-Stranded DNA Binding and Deamination. Biochemistry. 58(37). 3838–3847. 10 indexed citations
15.
Zheng, Jie, Chen Wang, Mi Ra Chang, et al.. (2018). HDX-MS reveals dysregulated checkpoints that compromise discrimination against self RNA during RIG-I mediated autoimmunity. Nature Communications. 9(1). 5366–5366. 30 indexed citations
16.
Devarkar, Swapnil C., et al.. (2018). RIG-I Uses an ATPase-Powered Translocation-Throttling Mechanism for Kinetic Proofreading of RNAs and Oligomerization. Molecular Cell. 72(2). 355–368.e4. 53 indexed citations
17.
Devarkar, Swapnil C., Chen Wang, Matthew T. Miller, et al.. (2016). Structural basis for m7G recognition and 2′-O-methyl discrimination in capped RNAs by the innate immune receptor RIG-I. Proceedings of the National Academy of Sciences. 113(3). 596–601. 257 indexed citations
18.
Ramanathan, Anand, Swapnil C. Devarkar, Fuguo Jiang, et al.. (2015). The autoinhibitory CARD2-Hel2i Interface of RIG-I governs RNA selection. Nucleic Acids Research. 44(2). 896–909. 30 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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