Ragul Gowthaman

2.5k total citations
27 papers, 845 citations indexed

About

Ragul Gowthaman is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Ragul Gowthaman has authored 27 papers receiving a total of 845 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 7 papers in Immunology and 4 papers in Infectious Diseases. Recurrent topics in Ragul Gowthaman's work include Immune Cell Function and Interaction (7 papers), vaccines and immunoinformatics approaches (7 papers) and T-cell and B-cell Immunology (6 papers). Ragul Gowthaman is often cited by papers focused on Immune Cell Function and Interaction (7 papers), vaccines and immunoinformatics approaches (7 papers) and T-cell and B-cell Immunology (6 papers). Ragul Gowthaman collaborates with scholars based in United States, India and China. Ragul Gowthaman's co-authors include Brian G. Pierce, John Karanicolas, Roy A. Mariuzza, Rui Yin, Lan Lan, Johnathan D. Guest, Liang Xu, Xiaoqing Wu, Jeffrey Aubé and Lin Yi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Ragul Gowthaman

26 papers receiving 837 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ragul Gowthaman United States 16 547 243 166 138 93 27 845
Toby Passioura Japan 21 1.2k 2.2× 105 0.4× 303 1.8× 213 1.5× 94 1.0× 50 1.5k
Nikita V. Ivanisenko Russia 18 484 0.9× 126 0.5× 82 0.5× 101 0.7× 57 0.6× 61 715
Peter Habenberger Germany 11 846 1.5× 472 1.9× 44 0.3× 118 0.9× 69 0.7× 17 1.3k
Bie Verbist Belgium 10 416 0.8× 229 0.9× 106 0.6× 369 2.7× 72 0.8× 26 1.0k
Micah Steffek United States 16 459 0.8× 363 1.5× 142 0.9× 101 0.7× 96 1.0× 20 991
Audrey Baker United States 13 585 1.1× 94 0.4× 129 0.8× 181 1.3× 41 0.4× 21 818
Marianna Dioszegi United States 10 244 0.4× 134 0.6× 185 1.1× 116 0.8× 119 1.3× 12 572
Jing An United States 20 638 1.2× 479 2.0× 143 0.9× 600 4.3× 59 0.6× 61 1.2k
Yu‐Hsien Chen United States 11 555 1.0× 485 2.0× 159 1.0× 240 1.7× 59 0.6× 15 954
Larissa Belov Australia 16 759 1.4× 191 0.8× 232 1.4× 192 1.4× 37 0.4× 37 1.1k

Countries citing papers authored by Ragul Gowthaman

Since Specialization
Citations

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

Fields of papers citing papers by Ragul Gowthaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ragul Gowthaman

This figure shows the co-authorship network connecting the top 25 collaborators of Ragul Gowthaman. A scholar is included among the top collaborators of Ragul Gowthaman 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 Ragul Gowthaman. Ragul Gowthaman 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.
Gowthaman, Ragul, Minjae Park, Rui Yin, Johnathan D. Guest, & Brian G. Pierce. (2025). AlphaFold and Docking Approaches for Antibody–Antigen and Other Targets: Insights From CAPRI Rounds 47–55. Proteins Structure Function and Bioinformatics. 2 indexed citations
2.
Lin, Valerie C. L., et al.. (2024). TCR3d 2.0: expanding the T cell receptor structure database with new structures, tools and interactions. Nucleic Acids Research. 53(D1). D604–D608. 9 indexed citations
3.
Wu, Daichao, A. V. Kolesnikov, Rui Yin, et al.. (2022). Structural assessment of HLA-A2-restricted SARS-CoV-2 spike epitopes recognized by public and private T-cell receptors. Nature Communications. 13(1). 27 indexed citations
4.
Yin, Rui, et al.. (2021). Structural and energetic profiling of SARS-CoV-2 receptor binding domain antibody recognition and the impact of circulating variants. PLoS Computational Biology. 17(9). e1009380–e1009380. 11 indexed citations
5.
Gowthaman, Ragul, Johnathan D. Guest, Rui Yin, et al.. (2020). CoV3D: a database of high resolution coronavirus protein structures. Nucleic Acids Research. 49(D1). D282–D287. 50 indexed citations
6.
Lan, Lan, Jiajun Liu, Amber R. Smith, et al.. (2020). Identification and Validation of an Aspergillus nidulans Secondary Metabolite Derivative as an Inhibitor of the Musashi-RNA Interaction. Cancers. 12(8). 2221–2221. 15 indexed citations
7.
Wu, Xiaoqing, Lan Lan, Shuang Han, et al.. (2020). Targeting the interaction between RNA-binding protein HuR and FOXQ1 suppresses breast cancer invasion and metastasis. Communications Biology. 3(1). 193–193. 80 indexed citations
8.
Wu, Daichao, D. Travis Gallagher, Ragul Gowthaman, Brian G. Pierce, & Roy A. Mariuzza. (2020). Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen. Nature Communications. 11(1). 2908–2908. 45 indexed citations
9.
Singh, Nishant K., Esam T. Abualrous, Cory M. Ayres, et al.. (2019). Geometrical characterization of T cell receptor binding modes reveals class‐specific binding to maximize access to antigen. Proteins Structure Function and Bioinformatics. 88(3). 503–513. 22 indexed citations
10.
Rangarajan, Sneha, Yanan He, Yi-Hong Chen, et al.. (2018). Peptide–MHC (pMHC) binding to a human antiviral T cell receptor induces long-range allosteric communication between pMHC- and CD3-binding sites. Journal of Biological Chemistry. 293(41). 15991–16005. 41 indexed citations
11.
Gowthaman, Ragul & Brian G. Pierce. (2018). TCRmodel: high resolution modeling of T cell receptors from sequence. Nucleic Acids Research. 46(W1). W396–W401. 48 indexed citations
12.
Lan, Lan, Hao Liu, Amber R. Smith, et al.. (2018). Natural product derivative Gossypolone inhibits Musashi family of RNA-binding proteins. BMC Cancer. 18(1). 809–809. 28 indexed citations
13.
Gowthaman, Ragul, Sergey Lyskov, & John Karanicolas. (2015). DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites. PLoS ONE. 10(7). e0131612–e0131612. 14 indexed citations
14.
Lan, Lan, Amber R. Smith, Jia Yu, et al.. (2015). Natural product (−)‐gossypol inhibits colon cancer cell growth by targeting RNA‐binding protein Musashi‐1. Molecular Oncology. 9(7). 1406–1420. 98 indexed citations
15.
Dixit, Anshuman, Lin Yi, Ragul Gowthaman, et al.. (2009). Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases. PLoS ONE. 4(10). e7485–e7485. 63 indexed citations
16.
Gowthaman, Ragul, et al.. (2007). TeCK Database: A comprehensive collection of telomeric and centromeric sequences with their associated proteins. Bioinformation. 2(2). 73–75. 3 indexed citations
17.
Gowthaman, Ragul, et al.. (2006). Computational screening of inhibitors for HIV-1 integrase using a receptor based pharmacophore model. Bioinformation. 1(4). 112–117. 5 indexed citations
18.
Gowthaman, Ragul, et al.. (2006). Modeling of the potential coiled-coil structure of snapin protein and its interaction with SNARE complex. Bioinformation. 1(7). 269–275. 5 indexed citations
19.
Gowthaman, Ragul, et al.. (2006). Database of cell signaling enzymes. Bioinformation. 1(7). 265–268.
20.
Gowthaman, Ragul, et al.. (2004). Distribution of proline-rich (PxxP) motifs in distinct proteomes: functional and therapeutic implications for malaria and tuberculosis. Protein Engineering Design and Selection. 17(2). 175–182. 47 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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