James D. Gorham

6.6k total citations · 2 hit papers
60 papers, 5.2k citations indexed

About

James D. Gorham is a scholar working on Immunology, Oncology and Hepatology. According to data from OpenAlex, James D. Gorham has authored 60 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Immunology, 16 papers in Oncology and 11 papers in Hepatology. Recurrent topics in James D. Gorham's work include T-cell and B-cell Immunology (13 papers), Immune Cell Function and Interaction (12 papers) and Cytokine Signaling Pathways and Interactions (10 papers). James D. Gorham is often cited by papers focused on T-cell and B-cell Immunology (13 papers), Immune Cell Function and Interaction (12 papers) and Cytokine Signaling Pathways and Interactions (10 papers). James D. Gorham collaborates with scholars based in United States, United Kingdom and France. James D. Gorham's co-authors include Carlo M. Croce, Elaine S. Jaffe, Yoshihide Tsujimoto, Jeffrey Cossman, Kenneth M. Murphy, Albert J. Czaja, Michael P. Manns, Simon C. Ling, Edward L. Krawitt and Giorgina Mieli‐Vergani and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

James D. Gorham

58 papers receiving 5.1k citations

Hit Papers

Diagnosis and Management of Autoi... 1985 2026 1998 2012 2010 1985 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James D. Gorham United States 29 1.9k 1.3k 1.2k 1.1k 923 60 5.2k
Giorgio Senaldi United States 37 2.2k 1.2× 1.8k 1.4× 633 0.5× 282 0.3× 858 0.9× 106 5.1k
Lishan Su United States 48 3.5k 1.8× 3.4k 2.7× 1.9k 1.5× 980 0.9× 1.3k 1.4× 184 8.8k
Fumihiko Ishikawa Japan 33 2.3k 1.2× 2.0k 1.6× 418 0.3× 261 0.2× 1.6k 1.8× 90 6.2k
Jochen Salfeld United States 20 1.9k 1.0× 1.6k 1.3× 1.3k 1.1× 512 0.5× 424 0.5× 29 4.7k
Minoru Nakamura Japan 36 1.2k 0.6× 663 0.5× 1.5k 1.2× 1.5k 1.4× 427 0.5× 130 3.9k
Salvatore Antonaci Italy 37 1000 0.5× 1.8k 1.4× 690 0.6× 1.0k 1.0× 1.1k 1.2× 189 4.4k
Karen Piper Hanley United Kingdom 44 1.1k 0.6× 2.2k 1.7× 513 0.4× 320 0.3× 640 0.7× 119 5.7k
Shie‐Liang Hsieh Taiwan 37 1.9k 1.0× 1.9k 1.5× 576 0.5× 188 0.2× 505 0.5× 109 5.3k
Lucy Golden‐Mason United States 38 2.5k 1.3× 852 0.7× 1.4k 1.1× 1.5k 1.4× 692 0.7× 88 4.5k
Leonie S. Taams United Kingdom 43 4.8k 2.5× 1.0k 0.8× 565 0.5× 262 0.2× 928 1.0× 100 7.0k

Countries citing papers authored by James D. Gorham

Since Specialization
Citations

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

Fields of papers citing papers by James D. Gorham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James D. Gorham. 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 James D. Gorham. The network helps show where James D. Gorham may publish in the future.

Co-authorship network of co-authors of James D. Gorham

This figure shows the co-authorship network connecting the top 25 collaborators of James D. Gorham. A scholar is included among the top collaborators of James D. Gorham 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 James D. Gorham. James D. Gorham 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.
Sekela, Michael, Edward L. Snyder, Ian J. Welsby, et al.. (2025). Transfusion of Amustaline/Glutathione Pathogen-reduced Red Blood Cells in Cardiac Surgery: A Randomized Phase 3 Clinical Trial. Anesthesiology. 143(5). 1196–1210.
2.
Howie, Heather L., Ariel Hay, Hayley R. Waterman, et al.. (2019). Differences in Steap3 expression are a mechanism of genetic variation of RBC storage and oxidative damage in mice. Blood Advances. 3(15). 2272–2285. 67 indexed citations
3.
Gorham, James D., et al.. (2012). 1 + 1 = 3: Development and Validation of a SNP-Based Algorithm to Identify Genetic Contributions from Three Distinct Inbred Mouse Strains. Journal of Biomolecular Techniques JBT. 23(4). jbt.12–2304. 1 indexed citations
4.
Cripps, James G., et al.. (2012). Liver inflammation in a mouse model of Th1 hepatitis despite the absence of invariant NKT cells or the Th1 chemokine receptors CXCR3 and CCR5. Laboratory Investigation. 92(10). 1461–1471. 5 indexed citations
5.
Cripps, James G. & James D. Gorham. (2011). MDSC in autoimmunity. International Immunopharmacology. 11(7). 789–793. 116 indexed citations
6.
Cripps, James G., et al.. (2010). Type 1 T Helper Cells Induce the Accumulation of Myeloid-Derived Suppressor Cells in the Inflamed Tgfb1 Knockout Mouse Liver. Hepatology. 52(4). 1350–1359. 77 indexed citations
7.
Milks, M. Wesley, James G. Cripps, Heping Lin, et al.. (2009). The role of Ifng in alterations in liver gene expression in a mouse model of fulminant autoimmune hepatitis. Liver International. 29(9). 1307–1315. 10 indexed citations
8.
Callaghan, Amanda, et al.. (2005). Resistance is costly: trade-offs between immunity, fecundity and survival in the pea aphid. Proceedings of the Royal Society B Biological Sciences. 272(1574). 1803–1808. 88 indexed citations
9.
Shultz, Leonard D., et al.. (2005). TGF-β1 Inhibits T-bet Induction by IFN-γ in Murine CD4+ T Cells through the Protein Tyrosine Phosphatase Src Homology Region 2 Domain-Containing Phosphatase-1. The Journal of Immunology. 175(9). 5666–5674. 77 indexed citations
10.
Gorham, James D.. (2005). Transforming growth factor‐β1, Th1 responses, and autoimmune liver disease. Transfusion. 45(s2). 51S–59S. 9 indexed citations
11.
Rudner, Lynnie A., Jack T. Lin, Il‐Kyoo Park, et al.. (2003). Necroinflammatory Liver Disease in BALB/c Background, TGF-β1-Deficient Mice Requires CD4+ T Cells. The Journal of Immunology. 170(9). 4785–4792. 34 indexed citations
12.
Sung, James L., Jack T. Lin, & James D. Gorham. (2003). CD28 co-stimulation regulates the effect of transforming growth factor-β1 on the proliferation of naıve CD4+ T cells. International Immunopharmacology. 3(2). 233–245. 37 indexed citations
13.
Gorham, James D., Jack T. Lin, James L. Sung, Lynnie A. Rudner, & Margaret A. French. (2001). Genetic Regulation of Autoimmune Disease: BALB/c Background TGF-β1-Deficient Mice Develop Necroinflammatory IFN-γ-Dependent Hepatitis. The Journal of Immunology. 166(10). 6413–6422. 75 indexed citations
14.
Gorham, James D., et al.. (2000). Dentistry. Open wide.. PubMed. 110(5728). 26–9. 2 indexed citations
15.
Güler, Mehmet, James D. Gorham, William F. Dietrich, et al.. (1999). Loci influencing development of Th responses. Identification from in vitro analysis. Microbes and Infection. 1(1). 79–88. 7 indexed citations
17.
Szabo, Susanne J., et al.. (1996). Regulation of Interleukin-12 Signalling During T Helper Phenotype Development. Advances in experimental medicine and biology. 409. 61–73. 22 indexed citations
18.
Szabo, Susanne J., et al.. (1995). Regulation of interleukin-12 signal transduction during T helper phenotype development. Research in Immunology. 146(7-8). 446–456. 13 indexed citations
19.
Gorham, James D., et al.. (1994). Evaluation of a New Colorimetric Assay for Serum Lithium. Therapeutic Drug Monitoring. 16(3). 277–280. 13 indexed citations
20.
Gorham, James D.. (1978). A medical triumph: the iron lung.. PubMed. 9(1). 71–3. 1 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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