A. Barr

2.6k citations
32 papers · 2.1k · h-index 20

Impact in

Papers in

    • Protein Tyrosine Phosphatases 14
    • Receptor Mechanisms and Signaling 7
    • Protein Kinase Regulation and GTPase Signaling 6
    • Glycosylation and Glycoproteins Research 3
    • ATP Synthase and ATPases Research 2
    • Galectins and Cancer Biology 12

A. Barr

29 papers receiving 2.1k citations

Peers

A. Barr
Comparison fields: 5 of 118
  • Toxicology 86
  • Immunology 490
  • Molecular Biology 1.6k
  • Cell Biology 235
  • Cellular and Molecular Neuroscience 259
Replace Christian Chabert with:
Christian Chabert United States
Sandra E. Wilkinson United Kingdom
Katsuhiko Ase Japan
Guriqbal S. Basi United States
Tyzoon Nomanbhoy United States
M. T. Bocquel France
G R Vandenbark United States
M. Berry France
Shuichan Xu United States
Kam C. Yeung United States
A. Barr relative to Christian Chabert United States Christian Chabert's profile →
Citations per field
00.5×1.5×2.1×
Christian Chabert · 1×
Citations per year

Countries citing papers authored by A. Barr

Since Specialization
Citations

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

Fields of papers citing papers by A. Barr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009386
2 1999294
3 2010234
4 2013208
5 1997162
6 2016124
7 199781
8 199856
9 200652
10 201451
11 200946
12 199345
13 200042
14 200638
15 201136
16 200036
17 201830
18 201028
19 199128
20 201826

About A. Barr

A. Barr is a scholar working on Molecular Biology, Immunology, Cellular and Molecular Neuroscience, Oncology and Genetics, having authored 32 papers that have together received 2.1k indexed citations. Recurring topics across this work include Protein Tyrosine Phosphatases (14 papers), Galectins and Cancer Biology (12 papers), Receptor Mechanisms and Signaling (7 papers), Protein Kinase Regulation and GTPase Signaling (6 papers), Glycosylation and Glycoproteins Research (3 papers), Neurobiology and Insect Physiology Research (3 papers), Neuroendocrine regulation and behavior (2 papers) and ATP Synthase and ATPases Research (2 papers). The work is most often cited by research in Toxicology (86 citations), Immunology (490 citations), Molecular Biology (1.6k citations), Cell Biology (235 citations) and Cellular and Molecular Neuroscience (259 citations). A. Barr has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include David R. Manning, Stefan Knapp, Lawrence F. Brass, Rolf T. Windh, E. Ugochukwu, Songzhu An, Timothy Hla, N. Burgess-Brown, Wen‐Hwa Lee and Steve P. Watson. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry, PLoS ONE, Future Medicinal Chemistry and Expert Systems with Applications.

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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