Stephen J. Hill

16.0k total citations · 3 hit papers
375 papers, 12.7k citations indexed

About

Stephen J. Hill is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Stephen J. Hill has authored 375 papers receiving a total of 12.7k indexed citations (citations by other indexed papers that have themselves been cited), including 239 papers in Molecular Biology, 118 papers in Cellular and Molecular Neuroscience and 84 papers in Physiology. Recurrent topics in Stephen J. Hill's work include Receptor Mechanisms and Signaling (178 papers), Adenosine and Purinergic Signaling (84 papers) and Neuropeptides and Animal Physiology (71 papers). Stephen J. Hill is often cited by papers focused on Receptor Mechanisms and Signaling (178 papers), Adenosine and Purinergic Signaling (84 papers) and Neuropeptides and Animal Physiology (71 papers). Stephen J. Hill collaborates with scholars based in United Kingdom, United States and Australia. Stephen J. Hill's co-authors include Stephen J. Briddon, Jillian G. Baker, J.M. Young, John M. Dickenson, Ian P. Hall, Laura E. Kilpatrick, Leigh A. Stoddart, Barrie Kellam, Thomas A. Edge and S P H Alexander and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Stephen J. Hill

367 papers receiving 12.3k citations

Hit Papers

International Union of Ph... 1990 2026 2002 2014 1997 1990 2018 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Stephen J. Hill 7.8k 3.5k 2.4k 1.7k 1.3k 375 12.7k
Koichi Suzuki 16.2k 2.1× 3.2k 0.9× 3.6k 1.5× 225 0.1× 2.6k 2.0× 902 30.7k
Peter Agre 25.7k 3.3× 2.6k 0.7× 750 0.3× 467 0.3× 5.2k 4.0× 233 34.9k
John W. Eaton 8.9k 1.1× 818 0.2× 1.8k 0.7× 303 0.2× 3.3k 2.5× 271 24.3k
Dennis Brown 15.8k 2.0× 961 0.3× 1.2k 0.5× 679 0.4× 2.3k 1.8× 366 23.4k
George Sachs 10.4k 1.3× 2.0k 0.6× 1.4k 0.6× 420 0.2× 1.0k 0.8× 456 20.3k
Pierluigi Nicotera 15.1k 1.9× 5.6k 1.6× 2.2k 0.9× 744 0.4× 3.4k 2.6× 248 26.4k
Bernd Mayer 7.3k 0.9× 3.3k 0.9× 1.6k 0.7× 294 0.2× 12.4k 9.4× 514 24.0k
Michael R. Duchen 14.2k 1.8× 4.6k 1.3× 1.1k 0.4× 792 0.5× 5.5k 4.2× 251 24.3k
Søren Nielsen 12.7k 1.6× 1.7k 0.5× 796 0.3× 219 0.1× 1.7k 1.3× 283 18.5k
Ernesto Carafoli 24.4k 3.1× 7.3k 2.1× 749 0.3× 1.7k 1.0× 4.2k 3.2× 493 33.3k

Countries citing papers authored by Stephen J. Hill

Since Specialization
Citations

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

Fields of papers citing papers by Stephen J. Hill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen J. Hill. 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 Stephen J. Hill. The network helps show where Stephen J. Hill may publish in the future.

Co-authorship network of co-authors of Stephen J. Hill

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen J. Hill. A scholar is included among the top collaborators of Stephen J. Hill 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 Stephen J. Hill. Stephen J. Hill 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
2.
White, Carl W., Laura E. Kilpatrick, Nicholas D. Kindon, et al.. (2024). CXCL17 is an allosteric inhibitor of CXCR4 through a mechanism of action involving glycosaminoglycans. Science Signaling. 17(828). eabl3758–eabl3758. 10 indexed citations
3.
Isidro‐Llobet, Albert, et al.. (2023). Characterisation of IL-23 receptor antagonists and disease relevant mutants using fluorescent probes. Nature Communications. 14(1). 2882–2882. 4 indexed citations
4.
Arimont, Marta, Meritxell Canals, Chris de Graaf, et al.. (2023). Small Molecule Fluorescent Ligands for the Atypical Chemokine Receptor 3 (ACKR3). ACS Medicinal Chemistry Letters. 15(1). 143–148. 3 indexed citations
5.
Kilpatrick, Laura E., et al.. (2022). Use of NanoBiT and NanoBRET to characterise interleukin‐23 receptor dimer formation in living cells. British Journal of Pharmacology. 180(11). 1444–1459. 3 indexed citations
6.
Hill, Stephen J., et al.. (2022). Involvement of β‐adrenoceptors in the cardiovascular responses induced by selective adenosine A 2A and A 2B receptor agonists. Pharmacology Research & Perspectives. 10(3). e00975–e00975. 3 indexed citations
7.
Veprintsev, Dmitry B., et al.. (2022). Kinetic analysis of endogenous β2‐adrenoceptor‐mediated cAMP GloSensor™ responses in HEK293 cells. British Journal of Pharmacology. 180(10). 1304–1315. 6 indexed citations
8.
Boyle, Eleanor, et al.. (2021). Role of the Renin–Angiotensin–Aldosterone and Kinin–Kallikrein Systems in the Cardiovascular Complications of COVID-19 and Long COVID. International Journal of Molecular Sciences. 22(15). 8255–8255. 48 indexed citations
9.
Leach, Katie, Stephen J. Hill, Joel D. A. Tyndall, et al.. (2021). Development of Covalent, Clickable Probes for Adenosine A1 and A3 Receptors. Journal of Medicinal Chemistry. 64(12). 8161–8178. 8 indexed citations
10.
Quynh, N., Priyank A. Shenoy, Tim Quach, et al.. (2021). A lipid-anchored neurokinin 1 receptor antagonist prolongs pain relief by a three-pronged mechanism of action targeting the receptor at the plasma membrane and in endosomes. Journal of Biological Chemistry. 296. 100345–100345. 15 indexed citations
11.
Soave, Mark, Raimond Heukers, Barrie Kellam, et al.. (2020). Monitoring Allosteric Interactions with CXCR4 Using NanoBiT Conjugated Nanobodies. Cell chemical biology. 27(10). 1250–1261.e5. 22 indexed citations
12.
Stoddart, Leigh A., Nicholas D. Kindon, Dmitry B. Veprintsev, et al.. (2020). Ligand-directed covalent labelling of a GPCR with a fluorescent tag in live cells. Communications Biology. 3(1). 722–722. 28 indexed citations
14.
Stoddart, Leigh A., Lizi Xia, Adriaan P. IJzerman, et al.. (2019). A live cell NanoBRET binding assay allows the study of ligand-binding kinetics to the adenosine A3 receptor. Purinergic Signalling. 15(2). 139–153. 33 indexed citations
15.
Soave, Mark, Stephen J. Briddon, Stephen J. Hill, & Leigh A. Stoddart. (2019). Fluorescent ligands: Bringing light to emerging GPCR paradigms. British Journal of Pharmacology. 177(5). 978–991. 57 indexed citations
16.
Peach, Chloe J., Laura E. Kilpatrick, Kris Zimmerman, et al.. (2018). Real-Time Ligand Binding of Fluorescent VEGF-A Isoforms that Discriminate between VEGFR2 and NRP1 in Living Cells. Cell chemical biology. 25(10). 1208–1218.e5. 28 indexed citations
17.
Kindon, Nicholas D., Jacqueline R. Glenn, Leigh A. Stoddart, et al.. (2018). Synthesis and Evaluation of the First Fluorescent Antagonists of the Human P2Y2 Receptor Based on AR-C118925. Journal of Medicinal Chemistry. 61(7). 3089–3113. 24 indexed citations
19.
Corriden, Ross, Tim Self, Victor Nizet, et al.. (2013). Adenosine‐A 3 receptors in neutrophil microdomains promote the formation of bacteria‐tethering cytonemes. EMBO Reports. 14(8). 726–732. 35 indexed citations
20.
Hill, Stephen J., et al.. (1998). The human adenosine A receptor activates the MAP kinase signalling pathway in transfected CHO-K1 cells. Nottingham Trent University's Institutional Repository (Nottingham Trent Repository). 1 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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