A. Barr
Impact in
- Molecular Biology top 5%
- Protein Tyrosine Phosphatases
- Sphingolipid Metabolism and Signaling
- Receptor Mechanisms and Signaling
- Protein Kinase Regulation and GTPase Signaling
- Hematology top 10%
- Platelet Disorders and Treatments
Papers in
-
- Protein Tyrosine Phosphatases 14
- Receptor Mechanisms and Signaling 7
- Protein Kinase Regulation and GTPase Signaling 5
- Sphingolipid Metabolism and Signaling 1
- Biochemical and Molecular Research 1
-
- Platelet Disorders and Treatments 3
- Co-authors
- David R. Manning (5 shared papers)Stefan Knapp (8 shared papers)E. Ugochukwu (3 shared papers)Lawrence F. Brass (1 shared paper)N. Burgess-Brown (2 shared papers)Rolf T. Windh (2 shared papers)Timothy Hla (1 shared paper)Songzhu Michael An (1 shared paper)
- Journals
- Journal of Biological Chemistry (4 papers)PLoS ONE (2 papers)Future Medicinal Chemistry (2 papers)Biochemistry (2 papers)Expert Systems with Applications (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
A. Barr
32 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 108
- Molecular Biology 1.4k
- Hematology 128
- Computational Theory and Mathematics 148
- Oncology 191
- Cellular and Molecular Neuroscience 130
Countries citing papers authored by A. Barr
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
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.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 399 | |
| 2 | 1999 | 296 | |
| 3 | 2010 | 241 | |
| 4 | 2013 | 213 | |
| 5 | 1997 | 157 | |
| 6 | 2016 | 130 | |
| 7 | 1997 | 79 | |
| 8 | 2014 | 59 | |
| 9 | 1998 | 56 | |
| 10 | 2006 | 56 | |
| 11 | 2019 | 52 | |
| 12 | 2009 | 47 | |
| 13 | 1993 | 45 | |
| 14 | 2000 | 41 | |
| 15 | 2006 | 41 | |
| 16 | 2011 | 40 | |
| 17 | 2018 | 40 | |
| 18 | 2000 | 37 | |
| 19 | 2018 | 30 | |
| 20 | 2018 | 29 |
About A. Barr
A. Barr is a scholar working on Molecular Biology, Hematology, Cellular and Molecular Neuroscience, Developmental Neuroscience and Oncology, having authored 34 papers that have together received 2.2k indexed citations. Recurring topics across this work include Protein Tyrosine Phosphatases (14 papers), Receptor Mechanisms and Signaling (7 papers), Protein Kinase Regulation and GTPase Signaling (5 papers), Platelet Disorders and Treatments (3 papers), Neuropeptides and Animal Physiology (3 papers), Metabolism and Genetic Disorders (1 paper), Sphingolipid Metabolism and Signaling (1 paper) and Biochemical and Molecular Research (1 paper). The work is most often cited by research in Molecular Biology (1.4k citations), Hematology (128 citations), Computational Theory and Mathematics (148 citations), Oncology (191 citations) and Cellular and Molecular Neuroscience (130 citations). A. Barr has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include David R. Manning, Stefan Knapp, E. Ugochukwu, Lawrence F. Brass, N. Burgess-Brown, Rolf T. Windh, Timothy Hla, Songzhu Michael An, Wen Hwa Lee and P. Filippakopoulos. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE, Future Medicinal Chemistry, Biochemistry 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.