David J. Kelvin

18.6k total citations · 3 hit papers
180 papers, 10.5k citations indexed

About

David J. Kelvin is a scholar working on Immunology, Epidemiology and Infectious Diseases. According to data from OpenAlex, David J. Kelvin has authored 180 papers receiving a total of 10.5k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Immunology, 44 papers in Epidemiology and 43 papers in Infectious Diseases. Recurrent topics in David J. Kelvin's work include Influenza Virus Research Studies (31 papers), T-cell and B-cell Immunology (28 papers) and Chemokine receptors and signaling (28 papers). David J. Kelvin is often cited by papers focused on Influenza Virus Research Studies (31 papers), T-cell and B-cell Immunology (28 papers) and Chemokine receptors and signaling (28 papers). David J. Kelvin collaborates with scholars based in Canada, United States and China. David J. Kelvin's co-authors include Joost J. Oppenheim, Andrew R. Lloyd, Dennis D. Taub, Kevin Conlon, Luoling Xu, Mark J. Cameron, Eric N. Olson, E A Sternberg, Lani A. Gossett and Salvatore Rubino and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

David J. Kelvin

178 papers receiving 10.3k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Recombinant human interferon-inducible protein 10 is a chemoattractant for human monocytes and T lymphocytes and promotes T cell adhesion to endothelial cells.

1993 675 citations David J. Kelvin, Joost J. Oppenheim et al. The Journal of Experimental Medicine profile →
Preferential Migration of Activated CD4 ⁺ and CD8 ⁺ T Cells in Response to MIP-1α and MIP-1β

1993 666 citations Joost J. Oppenheim, David J. Kelvin et al. profile →
A new myocyte-specific enhancer-binding factor that recognizes a conserved element associated with multiple muscle-specific genes.

1989 532 citations David J. Kelvin et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David J. Kelvin Canada	56	4.3k	3.0k	2.3k	2.0k	1.9k	180	10.5k
Mark R. Alderson United States	56	7.4k 1.7×	2.9k 1.0×	1.6k 0.7×	2.3k 1.1×	3.3k 1.7×	115	12.0k
Stephen K. Tyring United States	60	6.8k 1.6×	2.0k 0.7×	2.4k 1.1×	1.5k 0.7×	5.7k 3.0×	407	16.8k
Arne N. Akbar United Kingdom	75	11.1k 2.6×	3.0k 1.0×	2.6k 1.1×	951 0.5×	3.6k 1.9×	209	17.5k
David B. Lewis United States	52	4.6k 1.1×	1.9k 0.6×	850 0.4×	1.4k 0.7×	1.7k 0.9×	123	9.3k
Ulrich Kalinke Germany	58	8.2k 1.9×	3.8k 1.3×	2.1k 0.9×	2.1k 1.0×	2.3k 1.2×	241	14.1k
Brian L. Kotzin United States	59	8.5k 2.0×	1.7k 0.6×	1.4k 0.6×	1.2k 0.6×	1.3k 0.7×	175	13.5k
Eleanor N. Fish Canada	58	5.3k 1.3×	3.0k 1.0×	3.8k 1.7×	1.5k 0.8×	1.4k 0.7×	176	10.4k
Alan M. Krensky United States	70	9.5k 2.2×	3.3k 1.1×	2.2k 0.9×	1.3k 0.7×	1.8k 1.0×	228	15.8k
Stella C. Knight United Kingdom	53	6.9k 1.6×	2.5k 0.9×	1.7k 0.7×	772 0.4×	1.3k 0.7×	231	11.4k

Countries citing papers authored by David J. Kelvin

Since Specialization

Citations

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

Fields of papers citing papers by David J. Kelvin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Kelvin. 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 David J. Kelvin. The network helps show where David J. Kelvin may publish in the future.

Co-authorship network of co-authors of David J. Kelvin

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Kelvin. A scholar is included among the top collaborators of David J. Kelvin 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 David J. Kelvin. David J. Kelvin 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

Ostadgavahi, Ali Toloue, et al.. (2024). Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning. International Journal of Molecular Sciences. 25(11). 5920–5920. 2 indexed citations

Gadau, Sergio Domenico, et al.. (2024). Identification of 3-Aryl-1-benzotriazole-1-yl-acrylonitrile as a Microtubule-Targeting Agent (MTA) in Solid Tumors. International Journal of Molecular Sciences. 25(11). 5704–5704. 3 indexed citations

Murineddu, Gabriele, Gérard A. Pinna, Sonia Vanina Forcales, et al.. (2023). RNAseq Analysis of Novel 1,3,4-Oxadiazole Chalcogen Analogues Reveals Anti-Tubulin Properties on Cancer Cell Lines. International Journal of Molecular Sciences. 24(14). 11263–11263. 5 indexed citations

Ndishimye, Pacifique, Rachelle Buchanan, Sabin Nsanzimana, et al.. (2023). Third COVID-19 vaccine dose boosts antibody function in Rwandans with high HIV viral load. iScience. 26(10). 107959–107959. 3 indexed citations

Ostadgavahi, Ali Toloue, Ann Avery, Cheryl Cameron, et al.. (2022). An artificial neural network classification method employing longitudinally monitored immune biomarkers to predict the clinical outcome of critically ill COVID-19 patients. PeerJ. 10. e14487–e14487. 4 indexed citations

Medici, Serenella, et al.. (2021). Silver Nanoparticles Derived by Artemisia arborescens Reveal Anticancer and Apoptosis-Inducing Effects. International Journal of Molecular Sciences. 22(16). 8621–8621. 24 indexed citations

Zeng, Tiansheng, et al.. (2020). Target identification of a novel unsymmetrical 1,3,4‐oxadiazole derivative with antiproliferative properties. Journal of Cellular Physiology. 236(5). 3789–3799. 7 indexed citations

León, Alberto J., Viktoriya Borisevich, Robert L. Seymour, et al.. (2018). Host gene expression profiles in ferrets infected with genetically distinct henipavirus strains. PLoS neglected tropical diseases. 12(3). e0006343–e0006343. 23 indexed citations

Cameron, Mark J., Alyson A. Kelvin, Alberto J. León, et al.. (2012). Lack of Innate Interferon Responses during SARS Coronavirus Infection in a Vaccination and Reinfection Ferret Model. PLoS ONE. 7(9). e45842–e45842. 54 indexed citations

10.

Lanteri, Marion C., Katie M. O’Brien, Whitney E. Purtha, et al.. (2009). Tregs control the development of symptomatic West Nile virus infection in humans and mice. Journal of Clinical Investigation. 119(11). 3266–77. 176 indexed citations

11.

Riou, Catherine, Bader Yassine‐Diab, Julien van Grevenynghe, et al.. (2006). Convergence of TCR and cytokine signaling leads to FOXO3a phosphorylation and drives the survival of CD4+ central memory T cells. The Journal of Experimental Medicine. 204(1). 79–91. 179 indexed citations

12.

Wang, Hao, Mark E. DeVries, Bertha García, et al.. (2006). Regulation of B- and T-cell Mediated Xenogeneic Transplant Rejection by Interleukin 12. Transplantation. 81(2). 265–272. 5 indexed citations

13.

DeVries, Mark E., Alyson A. Kelvin, Luoling Xu, et al.. (2006). Defining the Origins and Evolution of the Chemokine/Chemokine Receptor System. The Journal of Immunology. 176(1). 401–415. 210 indexed citations

14.

Diao, Jun, Erin Winter, Wenhao Chen, et al.. (2006). In Situ Replication of Immediate Dendritic Cell (DC) Precursors Contributes to Conventional DC Homeostasis in Lymphoid Tissue. The Journal of Immunology. 176(12). 7196–7206. 87 indexed citations

15.

Lee, Boris P.-L., Elaine Mansfield, Tina Hernandez‐Boussard, et al.. (2005). Expression Profiling of Murine Double-Negative Regulatory T Cells Suggest Mechanisms for Prolonged Cardiac Allograft Survival. The Journal of Immunology. 174(8). 4535–4544. 30 indexed citations

16.

Sheth, Prameet M., Ali Danesh, Kamnoosh Shahabi, et al.. (2005). HIV-Specific CD8+ Lymphocytes in Semen Are Not Associated with Reduced HIV Shedding. The Journal of Immunology. 175(7). 4789–4796. 41 indexed citations

17.

Wang, Hao, Mark E. DeVries, Bertha García, et al.. (2005). CD80/CD86 Costimulation Regulates Acute Vascular Rejection. The Journal of Immunology. 175(9). 6197–6204. 18 indexed citations

18.

Wang, Hao, et al.. (2003). Attenuation of acute xenograft rejection by short-term treatment with LF15-0195 and monoclonal antibody against CD45RB in a rat-to-mouse cardiac transplantation model1. Transplantation. 75(9). 1475–1481. 14 indexed citations

19.

Wang, Hao, Wei‐Ping Min, Jinming Yang, et al.. (2003). Cytokines Regulate the Pattern of Rejection and Susceptibility to Cyclosporine Therapy in Different Mouse Recipient Strains After Cardiac Allografting. The Journal of Immunology. 171(7). 3823–3836. 56 indexed citations

20.

Johnston, James A., et al.. (1994). Staurosporine restores signaling and inhibits interleukin‐8‐induced chemotactic desensitization. European Journal of Immunology. 24(10). 2556–2562. 15 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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