Casey Beppler

1.2k citations
12 papers · 864 indexed · h-index 9

Impact in

  • Immunology top 10%
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology
    • Immune cells in cancer
    • Immune Cell Function and Interaction
  • Genetics top 5%
    • Glioma Diagnosis and Treatment

Papers in

    • Protein Structure and Dynamics 2
    • Single-cell and spatial transcriptomics 1
    • T-cell and B-cell Immunology 4
    • Immunotherapy and Immune Responses 3

Casey Beppler

11 papers receiving 860 citations

Peers

Casey Beppler
Comparison fields: 5 of 97
  • Immunology 405
  • Genetics 160
  • Molecular Medicine 48
  • Oncology 235
  • Cancer Research 114
Replace Daniela Schilling with:
Daniela Schilling Germany
M. Inoue Japan
Alexis Verger France
David Baillat United States
Gurunadh R. Chichili United States
Norvin D. Fernandes United States
Abdelouahid Maghnouj Germany
Kanika Bajaj Pahuja India
G. Jawahar Swaminathan United Kingdom
Antony Fearns United Kingdom
Casey Beppler relative to Daniela Schilling Germany Daniela Schilling's profile →
Citations per field
00.5×2.8×
Daniela Schilling · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Casey Beppler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Casey Beppler Line = papers co-authored together Casey Beppler links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2017309
2 2017200
3 2020160
4 201463
5 201650
6 201632
7 201723
8 202210
9 202210
10 20146
11 20161
12 20180

About Casey Beppler

Casey Beppler is a scholar working on Molecular Biology, Immunology, Genetics, Oncology and Molecular Medicine, having authored 12 papers that have together received 864 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (4 papers), Immunotherapy and Immune Responses (3 papers), Evolution and Genetic Dynamics (3 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), CAR-T cell therapy research (2 papers), Protein Structure and Dynamics (2 papers), Antibiotic Resistance in Bacteria (2 papers) and Single-cell and spatial transcriptomics (1 paper). The work is most often cited by research in Immunology (405 citations), Genetics (160 citations), Molecular Medicine (48 citations), Oncology (235 citations) and Cancer Research (114 citations). Casey Beppler has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Matthew F. Krummel, En Cai, Pamela J. Yeh, Zhiyuan Mao, Diego Carrera, Rolf Warta, Shruti Shrivastav, J Costello, Christel Herold‐Mende and Nduka Amankulor. Their work appears in journals such as Journal of The Royal Society Interface, The Journal of Cell Biology, Journal of Bacteriology, BMC Microbiology and Science.

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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