Kenneth Barr

1.2k citations
16 papers · 583 · h-index 11

Impact in

  • Immunology top 10%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • IL-33, ST2, and ILC Pathways
    • Immunotherapy and Immune Responses
    • CAR-T cell therapy research

Papers in

    • Genomics and Chromatin Dynamics 7
    • Single-cell and spatial transcriptomics 5
    • Gene Regulatory Network Analysis 5
    • RNA Research and Splicing 4
    • CRISPR and Genetic Engineering 4
    • Immune Cell Function and Interaction 4
    • T-cell and B-cell Immunology 3

Kenneth Barr

16 papers receiving 582 citations

Peers

Kenneth Barr
Comparison fields: 5 of 75
  • Immunology 340
  • Oncology 89
  • Genetics 84
  • Molecular Biology 192
  • Biophysics 14
Replace Klas Hatje with:
Klas Hatje Germany
Karl Garsha United States
Inna Averbukh Israel
Weike Pei China
Matej Krajcovic United States
Stephen H. Kazakoff Australia
Ruiqiong Wu United States
Alejandro Barrera United States
Kevin Van Bortle United States
Miyuki Nishimura Japan
Kenneth Barr relative to Klas Hatje Germany Klas Hatje's profile →
Citations per field
00.5×1.5×2.4×
Klas Hatje · 1×
Citations per year

Countries citing papers authored by Kenneth Barr

Since Specialization
Citations

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

Fields of papers citing papers by Kenneth Barr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2012170
2 2011150
3 201860
4 202045
5 202236
6 201332
7 202021
8 202114
9 201710
10 201310
11 202310
12 20179
13 20218
14 20195
15 20242
16 20131

About Kenneth Barr

Kenneth Barr is a scholar working on Molecular Biology, Immunology, Oncology, Ecology, Evolution, Behavior and Systematics and Genetics, having authored 16 papers that have together received 583 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (7 papers), Single-cell and spatial transcriptomics (5 papers), Gene Regulatory Network Analysis (5 papers), RNA Research and Splicing (4 papers), CRISPR and Genetic Engineering (4 papers), Immune Cell Function and Interaction (4 papers), CAR-T cell therapy research (3 papers) and T-cell and B-cell Immunology (3 papers). The work is most often cited by research in Immunology (340 citations), Oncology (89 citations), Genetics (84 citations), Molecular Biology (192 citations) and Biophysics (14 citations). Kenneth Barr has collaborated with scholars based in United States, South Korea and Brazil. Frequent co-authors include Fanyong Meng, Rebecca Mathew, Michael P. Seiler, Albert Bendelac, Chauncey J. Spooner, Megan K. Liszewski, Klaus Griewank, John Reinitz, Seddon Y. Thomas and Seth Thomas Scanlon. Their work appears in journals such as eLife, Molecular Immunology, Methods, Cell Genomics and Current Biology.

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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