Corey Tan

1.6k total citations · 1 hit paper
23 papers, 1.0k citations indexed

About

Corey Tan is a scholar working on Immunology, Nuclear and High Energy Physics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Corey Tan has authored 23 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Immunology, 8 papers in Nuclear and High Energy Physics and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Corey Tan's work include Particle physics theoretical and experimental studies (6 papers), T-cell and B-cell Immunology (6 papers) and Immune Cell Function and Interaction (5 papers). Corey Tan is often cited by papers focused on Particle physics theoretical and experimental studies (6 papers), T-cell and B-cell Immunology (6 papers) and Immune Cell Function and Interaction (5 papers). Corey Tan collaborates with scholars based in United States, Norway and United Kingdom. Corey Tan's co-authors include A. Capella, U. Sukhatme, J. Trân Thanh Vân, Julie Zikherman, Matthew J. Strassler, Richard C. Brower, John Huizar, Mark Noviski, James L. Mueller and Dennis Silverman and has published in prestigious journals such as Nature Immunology, The Journal of Immunology and Hepatology.

In The Last Decade

Corey Tan

23 papers receiving 974 citations

Hit Papers

Dual parton model 1994 2026 2004 2015 1994 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Corey Tan United States 15 648 200 113 65 53 23 1.0k
Y. Tomita Japan 15 261 0.4× 454 2.3× 126 1.1× 89 1.4× 269 5.1× 69 1.2k
H. Miyazawa Japan 12 218 0.3× 86 0.4× 10 0.1× 48 0.7× 240 4.5× 46 655
P. Jovanović Serbia 21 341 0.5× 119 0.6× 565 5.0× 10 0.2× 105 2.0× 130 1.6k
Yuji Sugawara Japan 20 454 0.7× 138 0.7× 221 2.0× 4 0.1× 126 2.4× 84 1.1k
J. Koponen United Kingdom 26 1.4k 2.1× 77 0.4× 105 0.9× 6 0.1× 50 0.9× 84 1.7k
R. C. Johnson United Kingdom 20 856 1.3× 186 0.9× 20 0.2× 6 0.1× 91 1.7× 50 1.5k
Paolo Angelino Switzerland 19 791 1.2× 79 0.4× 651 5.8× 4 0.1× 23 0.4× 44 1.1k
E. ̃Tassi Italy 18 182 0.3× 60 0.3× 106 0.9× 6 0.1× 32 0.6× 79 1.3k
Shirô Yoshida Japan 17 783 1.2× 98 0.5× 22 0.2× 4 0.1× 79 1.5× 54 1.2k
Tim C. de Wit Netherlands 17 522 0.8× 14 0.1× 455 4.0× 86 1.3× 16 0.3× 28 974

Countries citing papers authored by Corey Tan

Since Specialization
Citations

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

Fields of papers citing papers by Corey Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Corey Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Corey Tan. A scholar is included among the top collaborators of Corey Tan 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 Corey Tan. Corey Tan 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.
Astarita, Jillian L., Claudia X. Dominguez, Corey Tan, et al.. (2022). Treg specialization and functions beyond immune suppression. Clinical & Experimental Immunology. 211(2). 176–183. 30 indexed citations
2.
Brooks, Jeremy F., Corey Tan, James L. Mueller, et al.. (2021). Negative feedback by NUR77/Nr4a1 restrains B cell clonal dominance during early T-dependent immune responses. Cell Reports. 36(9). 109645–109645. 11 indexed citations
3.
Tan, Corey, Ryosuke Hiwa, James L. Mueller, et al.. (2020). NR4A nuclear receptors restrain B cell responses to antigen when second signals are absent or limiting. Nature Immunology. 21(10). 1267–1279. 49 indexed citations
4.
Mueller, James L., et al.. (2020). Synthetic Liposomal Mimics of Biological Viruses for the Study of Immune Responses to Infection and Vaccination. Bioconjugate Chemistry. 31(3). 685–697. 17 indexed citations
5.
Tan, Corey, James L. Mueller, Mark Noviski, et al.. (2019). Nur77 Links Chronic Antigen Stimulation to B Cell Tolerance by Restricting the Survival of Self-Reactive B Cells in the Periphery. The Journal of Immunology. 202(10). 2907–2923. 22 indexed citations
6.
Noviski, Mark, Corey Tan, John Huizar, et al.. (2019). Optimal Development of Mature B Cells Requires Recognition of Endogenous Antigens. The Journal of Immunology. 203(2). 418–428. 17 indexed citations
7.
Tan, Corey, Mark Noviski, John Huizar, & Julie Zikherman. (2019). Self‐reactivity on a spectrum: A sliding scale of peripheral B cell tolerance. Immunological Reviews. 292(1). 37–60. 34 indexed citations
8.
Berntsen, Natalie Lie, Bjarte Fosby, Corey Tan, et al.. (2018). Natural killer T cells mediate inflammation in the bile ducts. Mucosal Immunology. 11(6). 1582–1590. 16 indexed citations
9.
Huizar, John, Corey Tan, Mark Noviski, James L. Mueller, & Julie Zikherman. (2017). Nur77 Is Upregulated in B-1a Cells by Chronic Self-Antigen Stimulation and Limits Generation of Natural IgM Plasma Cells. ImmunoHorizons. 1(9). 188–197. 15 indexed citations
10.
Schrumpf, E., Xiaojun Jiang, Sebastian Zeißig, et al.. (2017). The role of natural killer T cells in a mouse model with spontaneous bile duct inflammation. Physiological Reports. 5(4). e13117–e13117. 10 indexed citations
11.
Schrumpf, E., Corey Tan, Tom H. Karlsen, et al.. (2015). The biliary epithelium presents antigens to and activates natural killer T cells. Hepatology. 62(4). 1249–1259. 74 indexed citations
12.
Tan, Corey. (2005). String / gauge duality and soft-hard pomeron. Acta Physica Polonica B. 36(2). 711–718. 2 indexed citations
13.
Levin, E., et al.. (2003). High energy amplitude as an admixture of ‘soft’ and ‘hard’ Pomerons. Nuclear Physics A. 732. 73–105. 9 indexed citations
14.
Capella, A., U. Sukhatme, Corey Tan, & J. Trân Thanh Vân. (1994). Dual parton model. Physics Reports. 236(4-5). 225–329. 420 indexed citations breakdown →
15.
Finkelstein, J., H. M. Fried, Kyung‐Ah Kang, & Corey Tan. (1989). Forward scattering at collider energies and eikonal unitarization of the odderon. Physics Letters B. 232(2). 257–262. 24 indexed citations
16.
Tan, Corey, et al.. (1987). Modular invariance of the thermo-partition function and global phase structure of the heterotic string. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 36(4). 1184–1192. 117 indexed citations
17.
Finkelstein, Julia L., et al.. (1985). A passion for physics: Essays in honor of Geoffrey Chew. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 14 indexed citations
18.
Gaisser, T. K., et al.. (1974). Is production peripheral or central?. Physics Letters B. 51(1). 83–86. 6 indexed citations
19.
Kang, Kyung‐Ah, et al.. (1972). Short-range correlations in two-particle productions. Physics Letters B. 38(2). 81–84. 4 indexed citations
20.
Silverman, Dennis & Corey Tan. (1971). Multiperipheral dynamics and inclusive experiments. Nuovo cimento della Società italiana di fisica. A, Nuclei, particles and fields. 2(2). 489–513. 29 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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