Casey Beppler

1.2k total citations
12 papers, 864 citations indexed

About

Casey Beppler is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Casey Beppler has authored 12 papers receiving a total of 864 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Genetics. Recurrent topics in Casey Beppler's work include T-cell and B-cell Immunology (4 papers), Immunotherapy and Immune Responses (3 papers) and Evolution and Genetic Dynamics (3 papers). Casey Beppler is often cited by papers focused on T-cell and B-cell Immunology (4 papers), Immunotherapy and Immune Responses (3 papers) and Evolution and Genetic Dynamics (3 papers). Casey Beppler collaborates with scholars based in United States, Spain and Germany. Casey Beppler's co-authors include En Cai, Matthew F. Krummel, Zhiyuan Mao, Pamela J. Yeh, Shruti Shrivastav, Payal Watchmaker, Nduka Amankulor, Christel Herold‐Mende, Diego Carrera and Naznin Jahan and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Casey Beppler

11 papers receiving 860 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Casey Beppler United States 9 405 276 235 160 114 12 864
Gabriele Matschiner Germany 14 383 0.9× 517 1.9× 123 0.5× 121 0.8× 56 0.5× 25 950
Daniela Schilling Germany 18 219 0.5× 638 2.3× 189 0.8× 60 0.4× 299 2.6× 47 1.1k
Atish Mohanty United States 16 88 0.2× 355 1.3× 218 0.9× 49 0.3× 101 0.9× 43 661
Chein‐Hung Chen Taiwan 16 379 0.9× 820 3.0× 207 0.9× 41 0.3× 59 0.5× 23 1.3k
Gurunadh R. Chichili United States 14 267 0.7× 525 1.9× 398 1.7× 35 0.2× 42 0.4× 23 1.1k
Emily C. Hartman United States 12 157 0.4× 1.3k 4.9× 450 1.9× 83 0.5× 53 0.5× 18 1.7k
Jean K. Stewart United States 6 323 0.8× 560 2.0× 193 0.8× 27 0.2× 71 0.6× 6 875
Edward B. Reilly United States 23 485 1.2× 590 2.1× 566 2.4× 157 1.0× 91 0.8× 54 2.1k
Andreas Maiser Germany 19 392 1.0× 1.2k 4.3× 117 0.5× 28 0.2× 90 0.8× 24 1.5k
Mary Ann Hardwicke United States 17 234 0.6× 636 2.3× 338 1.4× 52 0.3× 127 1.1× 24 1.4k

Countries citing papers authored by Casey Beppler

Since Specialization
Citations

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

Fields of papers citing papers by Casey Beppler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Casey Beppler

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

All Works

12 of 12 papers shown
1.
Beppler, Casey, En Cai, Carlos A. Castellanos, et al.. (2022). Hyperstabilization of T cell microvilli contacts by chimeric antigen receptors. The Journal of Cell Biology. 222(3). 10 indexed citations
2.
Cai, En, et al.. (2022). T cells use distinct topographical and membrane receptor scanning strategies that individually coalesce during receptor recognition. Proceedings of the National Academy of Sciences. 119(32). e2203247119–e2203247119. 10 indexed citations
3.
Ruhland, Megan K., Edward W. Roberts, En Cai, et al.. (2020). Visualizing Synaptic Transfer of Tumor Antigens among Dendritic Cells. Cancer Cell. 37(6). 786–799.e5. 160 indexed citations
4.
Cai, En, Peter Beemiller, Casey Beppler, et al.. (2018). Visualizing Dynamic Microvillar Search and Stabilization during Ligand Detection by T Cells. Biophysical Journal. 114(3). 547a–548a.
5.
Beppler, Casey, Elif Tekin, Zhiyuan Mao, et al.. (2017). When more is less: Emergent suppressive interactions in three-drug combinations. BMC Microbiology. 17(1). 107–107. 23 indexed citations
6.
Cai, En, Peter Beemiller, Casey Beppler, et al.. (2017). Visualizing dynamic microvillar search and stabilization during ligand detection by T cells. Science. 356(6338). 200 indexed citations
7.
Kohanbash, Gary, Diego Carrera, Shruti Shrivastav, et al.. (2017). Isocitrate dehydrogenase mutations suppress STAT1 and CD8+ T cell accumulation in gliomas. Journal of Clinical Investigation. 127(4). 1425–1437. 309 indexed citations
8.
Beppler, Casey, Elif Tekin, Zhiyuan Mao, et al.. (2016). Supplementary material from "Uncovering emergent interactions in three-way combinations of stressors". Figshare. 1 indexed citations
9.
Beppler, Casey, Elif Tekin, Zhiyuan Mao, et al.. (2016). Uncovering emergent interactions in three-way combinations of stressors. Journal of The Royal Society Interface. 13(125). 20160800–20160800. 32 indexed citations
10.
Tekin, Elif, et al.. (2016). Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs. Journal of The Royal Society Interface. 13(119). 20160332–20160332. 50 indexed citations
11.
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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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