Brian T. Abe

1.1k citations
16 papers · 611 · 1 hit paper · h-index 10

Impact in

    • MicroRNA in disease regulation
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses

Papers in

    • Signaling Pathways in Disease 5
    • Single-cell and spatial transcriptomics 2
    • RNA Interference and Gene Delivery 2
    • Immune Cell Function and Interaction 6
    • T-cell and B-cell Immunology 3

Brian T. Abe

15 papers receiving 598 citations

Brian T. Abe's Hit Papers

Engineering circular RNA for enhanced protein production 2022 · 271 citations
2710+1+2Years since publication50100150200250

Peers

Brian T. Abe
Comparison fields: 5 of 77
  • Cancer Research 155
  • Immunology 202
  • Molecular Biology 400
  • Oncology 79
  • Genetics 77
Replace Sandra Ussat with:
Sandra Ussat Germany
Fangzhou Lou China
Yixia Zhao China
Ling Qiu China
Lixia Miao China
Т. В. Наседкина Russia
Silvina Odete Bustos Brazil
Meera Shah United States
Guili Xu China
Brian T. Abe relative to Sandra Ussat Germany Sandra Ussat's profile →
Citations per field
00.5×10×15×18.1×
Sandra Ussat · 1×
Citations per year

Countries citing papers authored by Brian T. Abe

Since Specialization
Citations

This map shows the geographic impact of Brian T. Abe'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 Brian T. Abe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian T. Abe more than expected).

Fields of papers citing papers by Brian T. Abe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian T. Abe. 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 Brian T. Abe. The network helps show where Brian T. Abe may publish in the future.

Co-authors

The 25 scholars most cited alongside Brian T. Abe, 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 Brian T. Abe Line = papers co-authored together Brian T. Abe links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Engineering circular RNA for enhanced protein production
Hit paper breakdown →
2022271
2 200967
3 200962
4 202243
5 201942
6 201232
7 202324
8 201618
9 201314
10 20239
11 20248
12 20187
13 20176
14 20195
15 20093
16 20240

About Brian T. Abe

Brian T. Abe is a scholar working on Molecular Biology, Immunology, Genetics, Surgery and Oncology, having authored 16 papers that have together received 611 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (6 papers), Signaling Pathways in Disease (5 papers), Diabetes and associated disorders (4 papers), Pancreatic function and diabetes (3 papers), T-cell and B-cell Immunology (3 papers), Single-cell and spatial transcriptomics (2 papers), RNA Interference and Gene Delivery (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Cancer Research (155 citations), Immunology (202 citations), Molecular Biology (400 citations), Oncology (79 citations) and Genetics (77 citations). Brian T. Abe has collaborated with scholars based in United States, France and Switzerland. Frequent co-authors include Fernando Macián, Howard Y. Chang, Robert Chen, Ian Baine, Laura Amaya, Julia A. Belk, Paul A. Wender, Zhijian Li, Chun‐Kan Chen and Sean K. Wang. Their work appears in journals such as Molecular Cell, The Journal of Cell Biology, Diabetes, Analytical Chemistry and The Journal of Experimental Medicine.

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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