A. Barr

2.6k total citations
28 papers, 2.0k citations indexed

About

A. Barr is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, A. Barr has authored 28 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 12 papers in Immunology and 5 papers in Oncology. Recurrent topics in A. Barr's work include Protein Tyrosine Phosphatases (12 papers), Galectins and Cancer Biology (11 papers) and Receptor Mechanisms and Signaling (6 papers). A. Barr is often cited by papers focused on Protein Tyrosine Phosphatases (12 papers), Galectins and Cancer Biology (11 papers) and Receptor Mechanisms and Signaling (6 papers). A. Barr collaborates with scholars based in United Kingdom, United States and Canada. A. Barr's co-authors include David R. Manning, Stefan Knapp, Lawrence F. Brass, E. Ugochukwu, Rolf T. Windh, Timothy Hla, Songzhu An, N. Burgess-Brown, Wen‐Hwa Lee and Oliver N. F. King and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

A. Barr

28 papers receiving 2.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
A. Barr United Kingdom 20 1.6k 515 293 251 240 28 2.0k
Sandra E. Wilkinson United Kingdom 20 1.6k 1.0× 530 1.0× 368 1.3× 305 1.2× 173 0.7× 34 2.7k
Mario A. Pagano Italy 29 1.9k 1.2× 206 0.4× 368 1.3× 148 0.6× 311 1.3× 70 2.8k
Mir F. Ahmad United States 11 2.1k 1.3× 418 0.8× 465 1.6× 203 0.8× 364 1.5× 13 2.8k
Eileen M. McInerney United States 13 2.2k 1.4× 447 0.9× 739 2.5× 247 1.0× 71 0.3× 13 3.4k
Christine C. Hudson United States 12 2.1k 1.3× 244 0.5× 356 1.2× 204 0.8× 204 0.8× 16 2.7k
Christopher J. Caunt United Kingdom 25 1.5k 1.0× 251 0.5× 317 1.1× 100 0.4× 246 1.0× 40 2.3k
Miles A. Pufall United States 23 1.7k 1.0× 350 0.7× 360 1.2× 103 0.4× 138 0.6× 41 2.5k
Kazuo Sekiguchi Japan 15 1.3k 0.8× 292 0.6× 222 0.8× 294 1.2× 218 0.9× 21 1.9k
Katsuhiko Ase Japan 19 1.7k 1.1× 315 0.6× 131 0.4× 441 1.8× 320 1.3× 25 2.4k
Xiao-kun Zhang United States 29 3.4k 2.1× 607 1.2× 352 1.2× 720 2.9× 165 0.7× 77 4.2k

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-authorship network of co-authors of A. Barr

This figure shows the co-authorship network connecting the top 25 collaborators of A. Barr. A scholar is included among the top collaborators of A. Barr based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with A. Barr. A. Barr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Senis, Yotis A. & A. Barr. (2018). Targeting Receptor-Type Protein Tyrosine Phosphatases with Biotherapeutics: Is Outside-in Better than Inside-Out?. Molecules. 23(3). 569–569. 28 indexed citations
2.
Barr, A., et al.. (2017). Defining the molecular basis of interaction between R3 receptor-type protein tyrosine phosphatases and VE-cadherin. PLoS ONE. 12(9). e0184574–e0184574. 3 indexed citations
3.
García‐Rodríguez, José, Alberto García-García, Horacio Pérez‐Sánchez, et al.. (2016). Automatic selection of molecular descriptors using random forest: Application to drug discovery. Expert Systems with Applications. 72. 151–159. 112 indexed citations
4.
Ellison, Stuart, Jun Mori, A. Barr, & Yotis A. Senis. (2010). CD148 enhances platelet responsiveness to collagen by maintaining a pool of active Src family kinases. Journal of Thrombosis and Haemostasis. 8(7). 1575–1583. 27 indexed citations
5.
Hurley, Michael J., et al.. (2010). Receptor tyrosine phosphatase PTPγ is a regulator of spinal cord neurogenesis. Molecular and Cellular Neuroscience. 46(2). 469–482. 10 indexed citations
6.
Gingras, Marie‐Claude, Yu Ling Zhang, Dmitri Kharitidi, et al.. (2009). HD-PTP Is a Catalytically Inactive Tyrosine Phosphatase Due to a Conserved Divergence in Its Phosphatase Domain. PLoS ONE. 4(4). e5105–e5105. 44 indexed citations
7.
Barr, A., E. Ugochukwu, Wen‐Hwa Lee, et al.. (2009). Large-Scale Structural Analysis of the Classical Human Protein Tyrosine Phosphatome. Cell. 136(2). 352–363. 376 indexed citations
8.
Jeeves, Mark, et al.. (2008). Sequence-specific 1H, 13C and 15N backbone resonance assignments of the 34 kDa catalytic domain of human PTPN7. Biomolecular NMR Assignments. 2(2). 101–103. 9 indexed citations
9.
Eswaran, Jeyanthy, et al.. (2006). The crystal structure of human receptor protein tyrosine phosphatase κ phosphatase domain 1. Protein Science. 15(6). 1500–1505. 14 indexed citations
10.
Barr, A., J.E. Debreczeni, Jeyanthy Eswaran, & Stefan Knapp. (2006). Crystal structure of human protein tyrosine phosphatase 14 (PTPN14) at 1.65‐Å resolution. Proteins Structure Function and Bioinformatics. 63(4). 1132–1136. 13 indexed citations
11.
Barr, A. & Stefan Knapp. (2006). MAPK-specific tyrosine phosphatases: new targets for drug discovery?. Trends in Pharmacological Sciences. 27(10). 525–530. 36 indexed citations
12.
Eswaran, Jeyanthy, Brian D. Marsden, J.E. Debreczeni, et al.. (2006). Crystal structures and inhibitor identification for PTPN5, PTPRR and PTPN7: a family of human MAPK-specific protein tyrosine phosphatases. Biochemical Journal. 395(3). 483–491. 51 indexed citations
13.
Haribabu, Bodduluri, Ricardo M. Richardson, Margrith W. Verghese, et al.. (2000). Function and Regulation of Chemoattractant Receptors. Immunologic Research. 22(2-3). 271–280. 39 indexed citations
14.
Windh, Rolf T., et al.. (1999). Differential Coupling of the Sphingosine 1-Phosphate Receptors Edg-1, Edg-3, and H218/Edg-5 to the Gi, Gq, and G12 Families of Heterotrimeric G Proteins. Journal of Biological Chemistry. 274(39). 27351–27358. 288 indexed citations
15.
Ali, Hydar, Silvano Sozzani, Ian Fisher, et al.. (1998). Differential Regulation of Formyl Peptide and Platelet-activating Factor Receptors. Journal of Biological Chemistry. 273(18). 11012–11016. 55 indexed citations
16.
Barr, A., Lawrence F. Brass, & David R. Manning. (1997). Reconstitution of Receptors and GTP-binding Regulatory Proteins (G Proteins) in Sf9 Cells. Journal of Biological Chemistry. 272(4). 2223–2229. 156 indexed citations
17.
Barr, A. & David R. Manning. (1997). Agonist-independent Activation of Gz by the 5-Hydroxytryptamine1A Receptor Co-expressed in Spodoptera frugiperda Cells. Journal of Biological Chemistry. 272(52). 32979–32987. 76 indexed citations
18.
19.
Barr, A. & Steve P. Watson. (1993). Non‐peptide antagonists, CP‐96,345 and RP 67580, distinguish species variants in tachykinin NK1 receptors. British Journal of Pharmacology. 108(1). 223–227. 42 indexed citations
20.
Barr, A., Steve P. Watson, Andrés López Bernal, & Alan Nimmo. (1991). The presence of NK3 tachykinin receptors on rat uterus. European Journal of Pharmacology. 203(2). 287–290. 26 indexed citations

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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