David A. Fox

17.5k total citations · 4 hit papers
230 papers, 13.4k citations indexed

About

David A. Fox is a scholar working on Immunology, Rheumatology and Molecular Biology. According to data from OpenAlex, David A. Fox has authored 230 papers receiving a total of 13.4k indexed citations (citations by other indexed papers that have themselves been cited), including 124 papers in Immunology, 59 papers in Rheumatology and 47 papers in Molecular Biology. Recurrent topics in David A. Fox's work include T-cell and B-cell Immunology (67 papers), Immunotherapy and Immune Responses (40 papers) and Monoclonal and Polyclonal Antibodies Research (39 papers). David A. Fox is often cited by papers focused on T-cell and B-cell Immunology (67 papers), Immunotherapy and Immune Responses (40 papers) and Monoclonal and Polyclonal Antibodies Research (39 papers). David A. Fox collaborates with scholars based in United States, United Kingdom and Japan. David A. Fox's co-authors include Steven K. Lundy, Sujata Sarkar, Laura Tesmer, Ellis L. Reinherz, Stuart F. Schlossman, Judith Endres, Rebecca E. Hussey, Alison M. Gizinski, Oreste Acuto and David H. Katz and has published in prestigious journals such as New England Journal of Medicine, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

David A. Fox

223 papers receiving 13.0k citations

Hit Papers

NETs Are a Source of Citr... 1984 2026 1998 2012 2013 1984 2008 1985 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David A. Fox 6.7k 3.3k 3.2k 2.0k 1.6k 230 13.4k
Costantino Pitzalis 6.2k 0.9× 3.3k 1.0× 4.8k 1.5× 2.2k 1.1× 1.3k 0.8× 334 14.2k
Richard M. Pope 5.3k 0.8× 3.9k 1.2× 3.3k 1.0× 2.7k 1.3× 1.2k 0.7× 195 12.2k
Ranjeny Thomas 6.4k 1.0× 2.5k 0.8× 3.1k 1.0× 1.4k 0.7× 1.4k 0.9× 288 13.7k
Alisa E. Koch 4.7k 0.7× 4.9k 1.5× 3.5k 1.1× 3.8k 1.9× 1.1k 0.6× 182 14.1k
Nancy J. Olsen 4.8k 0.7× 2.5k 0.7× 4.5k 1.4× 1.3k 0.6× 1.5k 0.9× 240 12.6k
Fabienne Mackay 13.6k 2.0× 5.1k 1.5× 3.5k 1.1× 2.6k 1.3× 2.4k 1.5× 146 22.2k
G Steiner 3.6k 0.5× 3.9k 1.2× 5.6k 1.7× 2.1k 1.0× 1.7k 1.0× 286 11.7k
David S. Pisetsky 9.0k 1.4× 5.1k 1.5× 4.2k 1.3× 1.3k 0.6× 2.5k 1.5× 356 17.1k
Reinhard Voll 8.0k 1.2× 4.5k 1.3× 3.1k 1.0× 1.6k 0.8× 1000 0.6× 244 13.7k
Keith B. Elkon 10.1k 1.5× 4.7k 1.4× 5.0k 1.6× 1.3k 0.6× 2.2k 1.3× 203 16.4k

Countries citing papers authored by David A. Fox

Since Specialization
Citations

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

Fields of papers citing papers by David A. Fox

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David A. Fox

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Fox. A scholar is included among the top collaborators of David A. Fox 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 A. Fox. David A. Fox 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.
Fox, David A., et al.. (2025). CD6 in Human Disease. Cells. 14(4). 272–272.
2.
Lin, Feng, et al.. (2025). Ligands of CD6: roles in the pathogenesis and treatment of cancer. Frontiers in Immunology. 15. 1528478–1528478. 1 indexed citations
3.
Wu, Qi, M. Asif Amin, Pei‐Suen Tsou, et al.. (2024). Activation of cytotoxic lymphocytes through CD6 enhances killing of cancer cells. Cancer Immunology Immunotherapy. 73(2). 34–34. 6 indexed citations
4.
Cooney, Laura A., Qian Xiao, Jason A. Mears, et al.. (2023). 230 Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin. Journal of Investigative Dermatology. 143(11). S371–S371. 1 indexed citations
6.
Amin, M. Asif, Phillip L. Campbell, Qi Wu, et al.. (2022). Inhibition of bromodomain extraterminal histone readers alleviates skin fibrosis in experimental models of scleroderma. JCI Insight. 7(9). 12 indexed citations
7.
Ruth, Jeffrey H., M. Asif Amin, Phillip L. Campbell, et al.. (2021). CD6 is a target for cancer immunotherapy. JCI Insight. 6(5). 34 indexed citations
8.
O’Neil, Liam J., Ana Barrera‐Vargas, Javier Merayo‐Chalico, et al.. (2020). Neutrophil-mediated carbamylation promotes articular damage in rheumatoid arthritis. Science Advances. 6(44). 81 indexed citations
9.
Zhang, Lingjun, Ping Huang, Thomas L. Saunders, et al.. (2019). Absence of complement component 3 does not prevent classical pathway–mediated hemolysis. Blood Advances. 3(12). 1808–1814. 10 indexed citations
10.
Carmona‐Rivera, Carmelo, Philip M. Carlucci, Erica Moore, et al.. (2017). Synovial fibroblast-neutrophil interactions promote pathogenic adaptive immunity in rheumatoid arthritis. Science Immunology. 2(10). 239 indexed citations
11.
Mao‐Draayer, Yang, Qi Wu, Qin Wang, et al.. (2017). Basic Immunological Profile Changes of SPMS Patients Treated with BAF312 (P1.384). Neurology. 88(16_supplement). 1 indexed citations
12.
Chung, Kevin C., Sandra V. Kotsis, Patricia B. Burns, et al.. (2016). Seven‐Year Outcomes of the Silicone Arthroplasty in Rheumatoid Arthritis Prospective Cohort Study. Arthritis Care & Research. 69(7). 973–981. 21 indexed citations
13.
Dennis, Glynn, Cécile Holweg, Sarah Kummerfeld, et al.. (2014). Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics. Arthritis Research & Therapy. 16(2). R90–R90. 265 indexed citations
14.
Tran, Chinh, Steven K. Lundy, & David A. Fox. (2005). Synovial biology and T cells in rheumatoid arthritis. Pathophysiology. 12(3). 183–189. 109 indexed citations
15.
Fox, David A., Sujata Sarkar, S. M. A. Abidi, et al.. (2004). Expression and Characterization of a Novel CD6 Ligand in Cells Derived from Joint and Epithelial Tissues. The Journal of Immunology. 173(10). 6125–6133. 31 indexed citations
16.
Gupta, Raj, Yoshitaka Morita, Xiaogang He, et al.. (2001). Effector Function of Resting T Cells: Activation of Synovial Fibroblasts. The Journal of Immunology. 166(4). 2270–2275. 90 indexed citations
17.
Kozarsky, Karen, et al.. (1995). A Method for Monoclonal Antibody Isotype Switching: Anti-CD60 V H Expression in a Heavy Chain-Deficient Hybridoma Variant. Hybridoma. 14(6). 597–601. 2 indexed citations
18.
Kozarsky, Karen, et al.. (1988). A novel pathway of human T lymphocyte activation. Identification by a monoclonal antibody generated against a rheumatoid synovial T cell line.. The Journal of Immunology. 140(11). 3758–3765. 55 indexed citations
19.
Boyd, E., Ruth Sanger, M.J.W. Faed, et al.. (1981). Clinical Genetics Society. Abstracts of scientific papers presented on 18 and 19 September 1980 in Aberdeen. Journal of Medical Genetics. 18(3). 218–224. 3 indexed citations
20.
Chiorazzi, Nicholas, David A. Fox, & David H. Katz. (1977). Hapten-specific IgE antibody responses in mice. VII. Conversion of IgE "non-responder" strains to IgE "responders" by elimination of suppressor T cell activity.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 118(1). 48–54. 97 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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