Jay Reddy

1.6k total citations
62 papers, 1.1k citations indexed

About

Jay Reddy is a scholar working on Immunology, Cardiology and Cardiovascular Medicine and Epidemiology. According to data from OpenAlex, Jay Reddy has authored 62 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Immunology, 28 papers in Cardiology and Cardiovascular Medicine and 16 papers in Epidemiology. Recurrent topics in Jay Reddy's work include Viral Infections and Immunology Research (28 papers), T-cell and B-cell Immunology (13 papers) and Immune Cell Function and Interaction (9 papers). Jay Reddy is often cited by papers focused on Viral Infections and Immunology Research (28 papers), T-cell and B-cell Immunology (13 papers) and Immune Cell Function and Interaction (9 papers). Jay Reddy collaborates with scholars based in United States, Denmark and Canada. Jay Reddy's co-authors include Chandirasegaran Massilamany, Ninaad Lasrado, Arunakumar Gangaplara, David Steffen, Jean-Jack M. Riethoven, Sally A. Huber, Iwona A. Buskiewicz, James D. Eudy, Noel Rose and Marjorie F. Lou and has published in prestigious journals such as The Journal of Immunology, PLoS ONE and Scientific Reports.

In The Last Decade

Jay Reddy

58 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jay Reddy United States 20 461 425 305 239 165 62 1.1k
Chandirasegaran Massilamany United States 17 315 0.7× 331 0.8× 227 0.7× 180 0.8× 117 0.7× 49 807
Arunakumar Gangaplara United States 16 234 0.5× 435 1.0× 253 0.8× 206 0.9× 87 0.5× 41 864
Christopher M. Carthy Canada 13 476 1.0× 299 0.7× 555 1.8× 78 0.3× 141 0.9× 14 1.1k
Martin J. Richer Canada 19 113 0.2× 719 1.7× 282 0.9× 207 0.9× 261 1.6× 46 1.3k
Tatiana Pushkarsky United States 19 93 0.2× 498 1.2× 735 2.4× 175 0.7× 377 2.3× 38 1.5k
Diana Kouiavskaia United States 17 255 0.6× 171 0.4× 223 0.7× 61 0.3× 207 1.3× 35 845
Sergio Covarrubias United States 14 154 0.3× 299 0.7× 780 2.6× 147 0.6× 81 0.5× 23 1.2k
Kate L. Graham Australia 22 136 0.3× 413 1.0× 244 0.8× 127 0.5× 334 2.0× 35 1.2k
Hideaki Tsuzuki Japan 19 472 1.0× 109 0.3× 337 1.1× 296 1.2× 592 3.6× 40 1.3k
David A. Rhodes United Kingdom 18 70 0.2× 961 2.3× 526 1.7× 174 0.7× 56 0.3× 24 1.6k

Countries citing papers authored by Jay Reddy

Since Specialization
Citations

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

Fields of papers citing papers by Jay Reddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jay Reddy

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Reddy. A scholar is included among the top collaborators of Jay Reddy 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 Jay Reddy. Jay Reddy 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.
Zinniel, Denise K., et al.. (2025). Metabolic Reprogramming in Response to Freund’s Adjuvants: Insights from Serum Metabolomics. Microorganisms. 13(3). 492–492. 2 indexed citations
2.
Liu, Baolong, Phuong Linh Nguyen, Xingzhi Li, et al.. (2024). Honey vesicle-like nanoparticles protect aged liver from non-alcoholic steatohepatitis. Acta Pharmaceutica Sinica B. 14(8). 3661–3679. 5 indexed citations
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Lasrado, Ninaad, et al.. (2023). Vaccines against Group B Coxsackieviruses and Their Importance. Vaccines. 11(2). 274–274. 11 indexed citations
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Lasrado, Ninaad, et al.. (2022). Dissecting the cellular landscape and transcriptome network in viral myocarditis by single-cell RNA sequencing. iScience. 25(3). 103865–103865. 23 indexed citations
9.
Lasrado, Ninaad, Arunakumar Gangaplara, Chandirasegaran Massilamany, et al.. (2021). Attenuated strain of CVB3 with a mutation in the CAR-interacting region protects against both myocarditis and pancreatitis. Scientific Reports. 11(1). 12432–12432. 19 indexed citations
10.
Lasrado, Ninaad, Chandirasegaran Massilamany, Arunakumar Gangaplara, et al.. (2020). Viral myocarditis involves the generation of autoreactive T cells with multiple antigen specificities that localize in lymphoid and non-lymphoid organs in the mouse model of CVB3 infection. Molecular Immunology. 124. 218–228. 22 indexed citations
11.
Topliff, Christina L., Jay Reddy, Chandirasegaran Massilamany, et al.. (2017). Type 2 BVDV Npro suppresses IFN-1 pathway signaling in bovine cells and augments BRSV replication. Virology. 507. 123–134. 17 indexed citations
12.
Massilamany, Chandirasegaran, Arunakumar Gangaplara, Guobin Kang, et al.. (2016). Identification of an Epitope from Adenine Nucleotide Translocator 1 That Induces Inflammation in Heart in A/J Mice. American Journal Of Pathology. 186(12). 3160–3175. 12 indexed citations
13.
Massilamany, Chandirasegaran, Arunakumar Gangaplara, Vahid Khalilzad-Sharghi, et al.. (2015). Localization of CD8 T cell epitope within cardiac myosin heavy chain-α334–352 that induces autoimmune myocarditis in A/J mice. International Journal of Cardiology. 202. 311–321. 22 indexed citations
14.
Massilamany, Chandirasegaran, Andreas Koenig, Jay Reddy, Sally A. Huber, & Iwona A. Buskiewicz. (2015). Autoimmunity in picornavirus infections. Current Opinion in Virology. 16. 8–14. 10 indexed citations
15.
Massilamany, Chandirasegaran, et al.. (2015). Versatility of using major histocompatibility complex class II dextramers for derivation and characterization of antigen-specific, autoreactive T cell hybridomas. Journal of Immunological Methods. 426. 86–94. 4 indexed citations
16.
Massilamany, Chandirasegaran, Arunakumar Gangaplara, & Jay Reddy. (2014). Intricacies of cardiac damage in coxsackievirus B3 infection: Implications for therapy. International Journal of Cardiology. 177(2). 330–339. 36 indexed citations
17.
Massilamany, Chandirasegaran, Francine Marciano‐Cabral, Bruno da Rocha-Azevedo, et al.. (2014). SJL Mice Infected with Acanthamoeba castellanii Develop Central Nervous System Autoimmunity through the Generation of Cross-Reactive T Cells for Myelin Antigens. PLoS ONE. 9(5). e98506–e98506. 15 indexed citations
18.
Massilamany, Chandirasegaran, Arunakumar Gangaplara, Hongjiu Dai, et al.. (2011). miR-27b*, an oxidative stress-responsive microRNA modulates nuclear factor-kB pathway in RAW 264.7 cells. Molecular and Cellular Biochemistry. 352(1-2). 181–188. 99 indexed citations
19.
Massilamany, Chandirasegaran, Bijaya Upadhyaya, Arunakumar Gangaplara, Charles Kuszynski, & Jay Reddy. (2011). Detection of autoreactive CD4 T cells using major histocompatibility complex class II dextramers. BMC Immunology. 12(1). 40–40. 37 indexed citations
20.
Massilamany, Chandirasegaran, David Steffen, & Jay Reddy. (2009). An epitope from Acanthamoeba castellanii that cross-react with proteolipid protein 139-151-reactive T cells induces autoimmune encephalomyelitis in SJL mice. Journal of Neuroimmunology. 219(1-2). 17–24. 31 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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