Sundararajan Jayaraman

2.9k total citations
89 papers, 2.3k citations indexed

About

Sundararajan Jayaraman is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, Sundararajan Jayaraman has authored 89 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Immunology, 19 papers in Molecular Biology and 18 papers in Genetics. Recurrent topics in Sundararajan Jayaraman's work include Immune Cell Function and Interaction (24 papers), T-cell and B-cell Immunology (22 papers) and Diabetes and associated disorders (10 papers). Sundararajan Jayaraman is often cited by papers focused on Immune Cell Function and Interaction (24 papers), T-cell and B-cell Immunology (22 papers) and Diabetes and associated disorders (10 papers). Sundararajan Jayaraman collaborates with scholars based in United States, India and Slovakia. Sundararajan Jayaraman's co-authors include Bellur S. Prabhakar, Martin E. Dorf, Parris R. Burd, Howard W. Rogers, Carla A. Martin, John Gordon, Ann M. Dvořàk, Stephen J. Galli, Stephen D. Wilson and Clifford J. Bellone and has published in prestigious journals such as The Journal of Experimental Medicine, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Sundararajan Jayaraman

87 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sundararajan Jayaraman United States 24 1.1k 630 346 328 225 89 2.3k
Jan H. Lupker France 17 832 0.7× 643 1.0× 246 0.7× 285 0.9× 135 0.6× 29 1.9k
Steven H. Zuckerman United States 29 1.1k 1.0× 818 1.3× 267 0.8× 236 0.7× 122 0.5× 81 2.7k
Susan Kaufman Canada 26 686 0.6× 1.1k 1.8× 289 0.8× 253 0.8× 160 0.7× 89 3.0k
Nobuhiro Nakano Japan 26 1.4k 1.3× 794 1.3× 425 1.2× 239 0.7× 441 2.0× 79 3.1k
Margrith W. Verghese United States 25 1.1k 1.0× 1.4k 2.3× 400 1.2× 191 0.6× 305 1.4× 37 3.0k
Marie‐Anne Bach France 26 949 0.8× 490 0.8× 202 0.6× 155 0.5× 156 0.7× 75 2.8k
J D Hulmes United States 20 913 0.8× 1.2k 2.0× 273 0.8× 203 0.6× 94 0.4× 30 2.8k
Frank Martiniuk United States 27 541 0.5× 797 1.3× 777 2.2× 256 0.8× 178 0.8× 78 2.5k
Catherine Fournier France 29 1.7k 1.5× 759 1.2× 588 1.7× 489 1.5× 310 1.4× 87 3.8k
Mirta Giordano Argentina 27 988 0.9× 669 1.1× 265 0.8× 100 0.3× 160 0.7× 93 2.4k

Countries citing papers authored by Sundararajan Jayaraman

Since Specialization
Citations

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

Fields of papers citing papers by Sundararajan Jayaraman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sundararajan Jayaraman

This figure shows the co-authorship network connecting the top 25 collaborators of Sundararajan Jayaraman. A scholar is included among the top collaborators of Sundararajan Jayaraman 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 Sundararajan Jayaraman. Sundararajan Jayaraman 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.
Jayaraman, Sundararajan, et al.. (2021). Epigenetic drug ameliorated type 1 diabetes via decreased generation of Th1 and Th17 subsets and restoration of self-tolerance in CD4+ T cells. International Immunopharmacology. 103. 108490–108490. 4 indexed citations
2.
Jayaraman, Sundararajan, et al.. (2020). Treatment of autoimmune encephalomyelitis with a histone deacetylase inhibitor: Analyzing the role of immune-response genes. SHILAP Revista de lepidopterología. 1. 19–19. 4 indexed citations
3.
Jayaraman, Sundararajan, et al.. (2019). DNA Hypermethylation does not Negatively Impact the Transcription of the TNF-α Gene in an Acute T-Cell Leukemia. Epigenomics. 11(16). 1753–1763. 3 indexed citations
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Jayaraman, Sundararajan, Sung Won Kwon, Rajvir Singh, et al.. (2010). Transfusion of Nonobese Diabetic Mice with Allogeneic Newborn Blood Ameliorates Autoimmune Diabetes and Modifies the Expression of Selected Immune Response Genes. The Journal of Immunology. 184(6). 3008–3015. 12 indexed citations
7.
Rao, A. Jagannadha, S. G. Ramachandra, Ramesh Vaidyanathan, et al.. (2009). Effect of chronic administration of Tamoxifen on fertility in male bonnet monkeys (Macaca radiata). Andrologia. 30(3). 129–132. 4 indexed citations
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Gill-Sharma, M. K., et al.. (1993). Effects of tamoxifen on the fertility of male rats. Reproduction. 99(2). 395–402. 51 indexed citations
10.
Jayaraman, Sundararajan, et al.. (1990). Enhancement of in vivo cell-mediated immune responses by three distinct cytokines.. The Journal of Immunology. 144(3). 942–951. 36 indexed citations
11.
Kuchroo, Vijay K., J K Steele, R M O'Hara, et al.. (1990). Relationships between antigen-specific helper and inducer suppressor T cell hybridomas.. The Journal of Immunology. 145(2). 438–448. 18 indexed citations
12.
Burd, Parris R., Howard W. Rogers, John Gordon, et al.. (1989). Interleukin 3-dependent and -independent mast cells stimulated with IgE and antigen express multiple cytokines.. The Journal of Experimental Medicine. 170(1). 245–257. 487 indexed citations
13.
Jayaraman, Sundararajan & Clifford J. Bellone. (1986). Idiotype-specific T suppressor factor alternatively interacts with a nonspecific T-acceptor-like cell to mediate immune suppression. Cellular Immunology. 101(2). 363–372. 3 indexed citations
14.
Jayaraman, Sundararajan, et al.. (1986). Interference in primate follicular maturation: an approach with inhibin for female contraception. Advances in Contraception. 2(4). 337–342. 2 indexed citations
15.
Ducoff, Howard S., et al.. (1984). Repair studies utilizing a fly-pupariation model of postmitotic cell response.. PubMed. 6. 249–52. 1 indexed citations
16.
Jayaraman, Sundararajan, et al.. (1983). Effect of Chronic Administration of Inhibin and Testosterone on Spermatogenesis in Adult Male Rats. Archives of Andrology. 10(3). 233–238. 1 indexed citations
17.
Jayaraman, Sundararajan, James E. Swierkosz, & Clifford J. Bellone. (1982). T cell replacing factor substitutes for an I-J+ idiotype-specific T helper cell.. The Journal of Experimental Medicine. 155(2). 641–646. 21 indexed citations
18.
Jayaraman, Sundararajan, et al.. (1978). Detection of cell-mediated immunity to sheep erythrocytes by the capillary migration inhibition technique in the lizard, Calotes versicolor.. PubMed. 34(2). 231–40. 7 indexed citations
19.
Jayaraman, Sundararajan, et al.. (1976). Serum human placental lactogen (HPL) levels in normal pregnancy.. PubMed. 26(1). 65–9. 1 indexed citations
20.
Jayaraman, Sundararajan, et al.. (1975). Oxytocinase production in perfused human placentome. American Journal of Obstetrics and Gynecology. 123(2). 215–216. 4 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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