John S. Shaw

2.7k total citations · 1 hit paper
34 papers, 2.2k citations indexed

About

John S. Shaw is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, John S. Shaw has authored 34 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 16 papers in Cellular and Molecular Neuroscience and 6 papers in Physiology. Recurrent topics in John S. Shaw's work include Receptor Mechanisms and Signaling (13 papers), Neuropeptides and Animal Physiology (13 papers) and Pharmacological Receptor Mechanisms and Effects (9 papers). John S. Shaw is often cited by papers focused on Receptor Mechanisms and Signaling (13 papers), Neuropeptides and Animal Physiology (13 papers) and Pharmacological Receptor Mechanisms and Effects (9 papers). John S. Shaw collaborates with scholars based in United Kingdom and United States. John S. Shaw's co-authors include Norman G. Bowery, David R. Hill, Adam Doble, Alan L. Hudson, M J Turnbull, Derek N. Middlemiss, Lynne Miller, Charlotte K. Williams, Charles Romain and Gerard Costello and has published in prestigious journals such as Nature, Journal of Molecular Biology and Macromolecules.

In The Last Decade

John S. Shaw

34 papers receiving 2.1k citations

Hit Papers

(–)Baclofen decreases neurotransmitter release in the mam... 1980 2026 1995 2010 1980 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John S. Shaw United Kingdom 21 1.3k 1.1k 431 263 160 34 2.2k
Ganesh A. Thakur United States 36 1.6k 1.3× 1.3k 1.2× 550 1.3× 324 1.2× 254 1.6× 131 3.6k
Alan Naylor United Kingdom 24 512 0.4× 597 0.6× 325 0.8× 683 2.6× 49 0.3× 72 2.1k
Jean E. Lachowicz United States 33 1.9k 1.5× 2.1k 2.0× 342 0.8× 764 2.9× 303 1.9× 84 4.3k
J.L. Morgat France 26 1.3k 1.0× 1.6k 1.5× 267 0.6× 167 0.6× 51 0.3× 78 2.8k
Datta E. Ponde United States 22 676 0.5× 370 0.3× 115 0.3× 284 1.1× 275 1.7× 34 2.3k
Hideaki Yano United States 26 919 0.7× 1.2k 1.1× 53 0.1× 52 0.2× 78 0.5× 47 1.9k
Timothy J. Desmond United States 24 918 0.7× 502 0.5× 193 0.4× 223 0.8× 442 2.8× 48 1.8k
Christophe Plisson United Kingdom 22 437 0.3× 558 0.5× 103 0.2× 255 1.0× 140 0.9× 57 1.4k
Grazia Lombardi Italy 29 792 0.6× 1.1k 1.0× 216 0.5× 212 0.8× 98 0.6× 66 2.3k
Corey R. Hopkins United States 36 1.6k 1.2× 2.6k 2.5× 208 0.5× 515 2.0× 120 0.8× 145 4.1k

Countries citing papers authored by John S. Shaw

Since Specialization
Citations

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

Fields of papers citing papers by John S. Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John S. Shaw. 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 John S. Shaw. The network helps show where John S. Shaw may publish in the future.

Co-authorship network of co-authors of John S. Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of John S. Shaw. A scholar is included among the top collaborators of John S. Shaw 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 John S. Shaw. John S. Shaw 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.
Cumming, John G., Howard Tucker, J.W. Oldfield, et al.. (2012). Balancing hERG affinity and absorption in the discovery of AZD5672, an orally active CCR5 antagonist for the treatment of rheumatoid arthritis. Bioorganic & Medicinal Chemistry Letters. 22(4). 1655–1659. 21 indexed citations
2.
Smith, Emily, Helen M. McGettrick, Michael Stone, et al.. (2008). Duffy antigen receptor for chemokines and CXCL5 are essential for the recruitment of neutrophils in a multicellular model of rheumatoid arthritis synovium. Arthritis & Rheumatism. 58(7). 1968–1973. 47 indexed citations
3.
Onuoha, Stanley Chukwudozie, S. Mukund, Blanka Sengerová, et al.. (2007). Mechanistic Studies on Hsp90 Inhibition by Ansamycin Derivatives. Journal of Molecular Biology. 372(2). 287–297. 46 indexed citations
4.
Shaw, John S., et al.. (2007). Influence of the pattern of jejunal distension on mesenteric afferent sensitivity in the anaesthetized rat. Neurogastroenterology & Motility. 20(2). 149–158. 32 indexed citations
5.
Cumming, John G., S Brown, Anne Cooper, et al.. (2006). Modulators of the human CCR5 receptor. Part 3: SAR of substituted 1-[3-(4-methanesulfonylphenyl)-3-phenylpropyl]-piperidinyl phenylacetamides. Bioorganic & Medicinal Chemistry Letters. 16(13). 3533–3536. 15 indexed citations
6.
Cumming, John G., Anne Cooper, Ken Grime, et al.. (2005). Modulators of the human CCR5 receptor. Part 2: SAR of substituted 1-(3,3-diphenylpropyl)-piperidinyl phenylacetamides. Bioorganic & Medicinal Chemistry Letters. 15(22). 5012–5015. 21 indexed citations
7.
Lally, Frank, Emily Smith, Andrew Filer, et al.. (2005). A novel mechanism of neutrophil recruitment in a coculture model of the rheumatoid synovium. Arthritis & Rheumatism. 52(11). 3460–3469. 95 indexed citations
8.
Shaw, John S., et al.. (1993). Differential sensitivity of antinociceptive assays to the bradykinin antagonist Hoe 140. British Journal of Pharmacology. 108(1). 209–213. 44 indexed citations
11.
Shaw, John S., et al.. (1990). The coexistence of adenosine A1 and A2 receptors in guinea-pig aorta. European Journal of Pharmacology. 190(3). 329–335. 41 indexed citations
12.
GALT, R. H. B., et al.. (1989). The xanthene-9-spiro-4'-piperidine nucleus as a probe for opiate activity. Journal of Medicinal Chemistry. 32(10). 2357–2362. 21 indexed citations
13.
Shaw, John S., et al.. (1989). ICI 204448: a κP‐opioid agonist with limited access to the CNS. British Journal of Pharmacology. 96(4). 986–992. 53 indexed citations
14.
Shaw, John S., et al.. (1988). The physiological relevance of low agonist affinity binding at opioid μ‐receptors. British Journal of Pharmacology. 94(2). 625–631. 35 indexed citations
15.
Shaw, John S., et al.. (1988). Differential sensitivity of antinociceptive tests to opioid agonists and partial agonists. British Journal of Pharmacology. 95(2). 578–584. 45 indexed citations
16.
Costello, Gerard, et al.. (1988). A novel series of potent and selective agonists at the opioid κ-receptor. European Journal of Pharmacology. 151(3). 475–478. 55 indexed citations
17.
Miller, Lynne, Michael J. Rance, John S. Shaw, & John R. Traynor. (1985). Conversion of dynorphin-(1-9) to [Leu5]enkephalin by the mouse vas deferens in vitro. European Journal of Pharmacology. 116(1-2). 159–163. 12 indexed citations
18.
Miller, Lynne & John S. Shaw. (1983). Multiple opiate receptors in the mouse vas deferens. European Journal of Pharmacology. 90(2-3). 257–261. 5 indexed citations
19.
Bowery, Norman G., Adam Doble, David R. Hill, et al.. (1980). β-Chlorophenyl GABA (Baclofen) is a selective ligand for a novel GABA receptor on nerve terminals. Brain Research Bulletin. 5. 497–502. 10 indexed citations
20.
Bowery, Norman G., David R. Hill, Alan L. Hudson, et al.. (1980). (–)Baclofen decreases neurotransmitter release in the mammalian CNS by an action at a novel GABA receptor. Nature. 283(5742). 92–94. 891 indexed citations breakdown →

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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