Jyothi Jayaraman

1.7k total citations
45 papers, 1.2k citations indexed

About

Jyothi Jayaraman is a scholar working on Immunology, Epidemiology and Infectious Diseases. According to data from OpenAlex, Jyothi Jayaraman has authored 45 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Immunology, 13 papers in Epidemiology and 9 papers in Infectious Diseases. Recurrent topics in Jyothi Jayaraman's work include Immune Cell Function and Interaction (18 papers), T-cell and B-cell Immunology (11 papers) and Nail Diseases and Treatments (9 papers). Jyothi Jayaraman is often cited by papers focused on Immune Cell Function and Interaction (18 papers), T-cell and B-cell Immunology (11 papers) and Nail Diseases and Treatments (9 papers). Jyothi Jayaraman collaborates with scholars based in India, United Kingdom and United States. Jyothi Jayaraman's co-authors include James A. Traherne, John Trowsdale, K.S. Joseph, Wei Jiang, Vivien Béziat, Karl‐Johan Malmberg, Stella Larsson, Lisa L. Liu, Monika Enqvist and Ashley Moffett and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Jyothi Jayaraman

42 papers receiving 1.1k citations

Peers

Jyothi Jayaraman

IMMUN

EPIDE

PHEOH

ONCOL

Andrea Introini United States

Christina Megli United States

Yann Fardini France

Archana Thomas United States

David J. C. Miles United Kingdom

Stefanie Henriet Netherlands

Elisa Tagliani Italy

Sharline Madera United States

Juliet Crabtree United States

Patrizia Puddu Italy

Andrea Introini United States

Jyothi Jayaraman

771 ×1.0

IMMUN

258 ×1.1

EPIDE

79 ×0.7

PHEOH

107 ×1.0

ONCOL

38 ×0.4

Citations per year, relative to Jyothi Jayaraman Jyothi Jayaraman (= 1×) peers Andrea Introini

Countries citing papers authored by Jyothi Jayaraman

Since Specialization

Citations

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

Fields of papers citing papers by Jyothi Jayaraman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jyothi Jayaraman

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

All Works

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20 of 20 papers shown

Jayaraman, Jyothi, et al.. (2025). Cutaneous Rosai–Dorfman Disease Mimicking Granulomatous Dermatoses: A Rare Case Report. Pediatric Dermatology. 43(1). 166–170. 1 indexed citations

Jayaraman, Jyothi, et al.. (2025). Antibiotic resistance and biofilm formation in Cutibacterium acnes: A descriptive cross-sectional study. Indian Journal of Dermatology Venereology and Leprology. 91(3). 315–320. 1 indexed citations

Bhat, RameshM, et al.. (2024). Immunohistochemical analysis of chronic and recurrent dermatophytosis. Mycoses. 67(3). e13714–e13714.

Jayaraman, Jyothi, et al.. (2023). Antibiogram study of Pasteurella multocida strains isolated from pneumonic sheep and goats in Warangal region of Telangana. International Journal of Veterinary Sciences and Animal Husbandry. 8(5). 85–87. 1 indexed citations

Bhat, RameshM, et al.. (2022). A case of spontaneously arising strangely shaped scars. JAAD Case Reports. 32. 5–7.

Shreeve, Norman, Delia Hawkes, James A. Traherne, et al.. (2021). The CD94/NKG2A inhibitory receptor educates uterine NK cells to optimize pregnancy outcomes in humans and mice. Immunity. 54(6). 1231–1244.e4. 61 indexed citations

Shenoy, Manjunath, Madhu Rengasamy, Sunil Dogra, et al.. (2020). Indian association of dermatologists, venereologists and leprologists (IADVL) task force against recalcitrant tinea (ITART) consensus on the management of glabrous tinea (INTACT). Indian Dermatology Online Journal. 11(4). 502–502. 45 indexed citations

Tukwasibwe, Stephen, Annettee Nakimuli, James A. Traherne, et al.. (2020). Variations in killer-cell immunoglobulin-like receptor and human leukocyte antigen genes and immunity to malaria. Cellular and Molecular Immunology. 17(8). 799–806. 21 indexed citations

Huhn, Oisín, Olympe Chazara, Martin A. Ivarsson, et al.. (2018). High-Resolution Genetic and Phenotypic Analysis of KIR2DL1 Alleles and Their Association with Pre-Eclampsia. The Journal of Immunology. 201(9). 2593–2601. 25 indexed citations

10.

Putty, Kalyani, et al.. (2018). Standardization and application of real-time polymerase chain reaction for rapid detection of bluetongue virus. Veterinary World. 11(4). 452–458. 13 indexed citations

11.

Hydes, Theresa, James A. Traherne, Jyothi Jayaraman, et al.. (2016). STAT4-associated natural killer cell tolerance following liver transplantation. Gut. 66(2). 352–361. 26 indexed citations

12.

Liu, Lisa L., Johannes Landskron, Eivind Heggernes Ask, et al.. (2016). Critical Role of CD2 Co-stimulation in Adaptive Natural Killer Cell Responses Revealed in NKG2C-Deficient Humans. Cell Reports. 15(5). 1088–1099. 174 indexed citations

13.

Jayaraman, Jyothi, et al.. (2015). Evaluation of the Utility of the Edmonton Symptom Assessment System (revised) Scale on a Tertiary Palliative Care Unit. Journal of Palliative Care. 31(1). 44–50. 5 indexed citations

14.

Guinan, Kieran J., Jyothi Jayaraman, James A. Traherne, et al.. (2015). 2DL1, 2DL2 and 2DL3 all contribute to KIR phenotype variability on human NK cells. Genes and Immunity. 16(5). 301–310. 33 indexed citations

15.

Pontikos, Nikolas, Deborah J. Smyth, Helen Schuilenburg, et al.. (2014). A hybrid qPCR/SNP array approach allows cost efficient assessment of KIR gene copy numbers in large samples. BMC Genomics. 15(1). 274–274. 13 indexed citations

16.

Roberts, Chrissy h., Wei Jiang, Jyothi Jayaraman, et al.. (2014). Killer-cell Immunoglobulin-like Receptor gene linkage and copy number variation analysis by droplet digital PCR. Genome Medicine. 6(3). 20–20. 31 indexed citations

17.

Nakimuli, Annettee, Olympe Chazara, Lydia Farrell, et al.. (2013). Killer cell immunoglobulin-like receptor (KIR) genes and their HLA-C ligands in a Ugandan population. Immunogenetics. 65(11). 765–775. 33 indexed citations

18.

Jayaraman, Jyothi & K.S. Joseph. (2013). Determinants of place of death: a population-based retrospective cohort study. BMC Palliative Care. 12(1). 19–19. 47 indexed citations

19.

Jiang, Wei, Christopher Johnson, Jyothi Jayaraman, et al.. (2012). Copy number variation leads to considerable diversity for B but not A haplotypes of the human KIR genes encoding NK cell receptors. Genome Research. 22(10). 1845–1854. 140 indexed citations

20.

George, Kuryan, Jasmin Prasad, Jayaprakash Muliyil, et al.. (2009). Perinatal outcomes in a South Asian setting with high rates of low birth weight. BMC Pregnancy and Childbirth. 9(1). 5–5. 20 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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