Jeff Subleski

743 total citations
15 papers, 640 citations indexed

About

Jeff Subleski is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Jeff Subleski has authored 15 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 4 papers in Molecular Biology and 3 papers in Oncology. Recurrent topics in Jeff Subleski's work include Immune Cell Function and Interaction (11 papers), Immunotherapy and Immune Responses (5 papers) and T-cell and B-cell Immunology (3 papers). Jeff Subleski is often cited by papers focused on Immune Cell Function and Interaction (11 papers), Immunotherapy and Immune Responses (5 papers) and T-cell and B-cell Immunology (3 papers). Jeff Subleski collaborates with scholars based in United States, Ireland and Germany. Jeff Subleski's co-authors include Paritosh Ghosh, Howard A. Young, John R. Ortaldo, Robert H. Wiltrout, Timothy Back, Marco Cippitelli, Joseph T. Bruder, Tse‐Hua Tan, Veronica L. Hall and Jenn‐Haung Lai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Blood.

In The Last Decade

Jeff Subleski

14 papers receiving 622 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jeff Subleski United States	11	474	221	167	123	33	15	640
Judith A. Horvath‐Arcidiacono United States	11	394 0.8×	186 0.8×	120 0.7×	54 0.4×	32 1.0×	14	599
Lixin Wang China	14	254 0.5×	217 1.0×	357 2.1×	87 0.7×	36 1.1×	29	657
Hiromoto Mizoguchi Japan	7	517 1.1×	271 1.2×	163 1.0×	58 0.5×	15 0.5×	7	748
SF Ziegler United States	10	393 0.8×	289 1.3×	135 0.8×	59 0.5×	27 0.8×	13	605
Niquiche Sangster‐Guity United States	8	359 0.8×	227 1.0×	237 1.4×	78 0.6×	21 0.6×	10	613
M Stefănescu Romania	11	212 0.4×	114 0.5×	174 1.0×	113 0.9×	25 0.8×	23	467
Junbo Hu China	11	213 0.4×	175 0.8×	199 1.2×	90 0.7×	17 0.5×	28	484
Xue F. Huang United States	13	301 0.6×	162 0.7×	291 1.7×	47 0.4×	33 1.0×	21	621
Prathyusha Gudapati United States	5	383 0.8×	132 0.6×	289 1.7×	51 0.4×	23 0.7×	10	594
Alaa Kassim Ali Canada	11	587 1.2×	256 1.2×	206 1.2×	87 0.7×	14 0.4×	19	780

Countries citing papers authored by Jeff Subleski

Since Specialization

Citations

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

Fields of papers citing papers by Jeff Subleski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeff Subleski

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

All Works

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15 of 15 papers shown

Subleski, Jeff, Erika M. Palmieri, Steven H. Hsu, et al.. (2026). Pyruvate kinase muscle 2 (PKM2) promotes CD4 T cell survival by regulating pyruvate oxidation during homeostasis and expansion. Science Advances. 12(5). eaec5092–eaec5092.

Ford, Jill, O. M. Zack Howard, Jeff Subleski, et al.. (2010). Enhanced Triggering Receptor Expressed on Myeloid Cells 1 (TREM-1) and Soluble TREM-1 Levels in the Myeloid Cells of Tumor-Bearing Mice and Patients with Renal Cell Carcinoma (100.8). The Journal of Immunology. 184(Supplement_1). 100.8–100.8. 1 indexed citations

Hodge, Deborah L., Jun Yang, Matthew D. Buschman, et al.. (2009). Interleukin-15 Enhances Proteasomal Degradation of Bid in Normal Lymphocytes: Implications for Large Granular Lymphocyte Leukemias. Cancer Research. 69(9). 3986–3994. 50 indexed citations

Weiss, Jonathan M., Timothy Back, Anthony J. Scarzello, et al.. (2009). Successful immunotherapy with IL-2/anti-CD40 induces the chemokine-mediated mitigation of an immunosuppressive tumor microenvironment. Proceedings of the National Academy of Sciences. 106(46). 19455–19460. 57 indexed citations

Subleski, Jeff, Veronica L. Hall, Jonathan M. Weiss, John R. Ortaldo, & Robert H. Wiltrout. (2007). Differential modulation of NK and NKT cells in the liver and spleen following IL-18 + IL-12 treatment of mice (98.9). The Journal of Immunology. 178(1_Supplement). S193–S193. 1 indexed citations

Hodge, Deborah L., Jeff Subleski, Della Reynolds, et al.. (2006). The Proinflammatory Cytokine Interleukin-18 Alters Multiple Signaling Pathways to Inhibit Natural Killer Cell Death. Journal of Interferon & Cytokine Research. 26(10). 706–718. 26 indexed citations

Subleski, Jeff, Veronica L. Hall, Timothy Back, John R. Ortaldo, & Robert H. Wiltrout. (2006). Enhanced Antitumor Response by Divergent Modulation of Natural Killer and Natural Killer T Cells in the Liver. Cancer Research. 66(22). 11005–11012. 71 indexed citations

Subleski, Jeff, et al.. (2004). Tumor regression by anti-CD40 and interleukin-2: role of CD40 in hematopoietic cells and organ-specific effects. Biology of Blood and Marrow Transplantation. 10(8). 534–539. 5 indexed citations

Zhang, Xia, María Cecilia Rodriguez‐Galán, Jeff Subleski, et al.. (2004). Peroxisome proliferator-activated receptor-γ and its ligands attenuate biologic functions of human natural killer cells. Blood. 104(10). 3276–3284. 39 indexed citations

10.

Murphy, William J., Timothy Back, Julie A. Hixon, et al.. (2003). Synergistic Anti-Tumor Responses After Administration of Agonistic Antibodies to CD40 and IL-2: Coordination of Dendritic and CD8+ Cell Responses. The Journal of Immunology. 170(5). 2727–2733. 84 indexed citations

11.

Nelson, Edward L., Susan Strobl, Jeff Subleski, et al.. (1999). Cycling of human dendritic cell effector phenotypes in response to TNF‐α: modification of the current ‘maturation’ paradigm and implications for in vivo immunoregulation. The FASEB Journal. 13(14). 2021–2030. 33 indexed citations

12.

Curiel, Rafael E., Riitta Lahesmaa, Jeff Subleski, et al.. (1997). Identification of a Stat‐6‐responsive element in the promoter of the human interleukin‐4 gene. European Journal of Immunology. 27(8). 1982–1987. 46 indexed citations

13.

Ghosh, Paritosh, Antonio Sica, Marco Cippitelli, et al.. (1996). Activation of Nuclear Factor of Activated T Cells in a Cyclosporin A-resistant Pathway. Journal of Biological Chemistry. 271(13). 7700–7704. 46 indexed citations

14.

Lai, Jenn‐Haung, et al.. (1995). RelA Is a Potent Transcriptional Activator of the CD28 Response Element within the Interleukin 2 Promoter. Molecular and Cellular Biology. 15(8). 4260–4271. 121 indexed citations

15.

Ye, Jianping, Paritosh Ghosh, Marco Cippitelli, et al.. (1994). Characterization of a silencer regulatory element in the human interferon-gamma promoter.. Journal of Biological Chemistry. 269(41). 25728–25734. 60 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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