Stephen Alexander
Impact in
- Pharmacology top 0.1%
- Cannabis and Cannabinoid Research
- Pharmacogenetics and Drug Metabolism
- Physiology top 0.2%
- Pain Mechanisms and Treatments
- Adenosine and Purinergic Signaling
Papers in
- Physiology 28
- Adenosine and Purinergic Signaling 28
- Pharmacology 44
- Cannabis and Cannabinoid Research 43
- Pharmacogenetics and Drug Metabolism 9
- Co-authors
- Elena Faccenda (44 shared papers)Adam J Pawson (42 shared papers)Joanna L Sharman (38 shared papers)John A. Peters (39 shared papers)Christopher Southan (37 shared papers)Jamie A. Davies (36 shared papers)Eamonn Kelly (28 shared papers)Helen E. Benson (20 shared papers)
- Journals
- British Journal of Pharmacology (125 papers)Journal of Neurochemistry (9 papers)Nucleic Acids Research (7 papers)Pharmacological Reviews (4 papers)The FASEB Journal (4 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Stephen Alexander
245 papers receiving 25.7k citations
Stephen Alexander's Hit Papers
Peers
Comparison fields: 5 of 155
- Pharmacology 4.1k
- Physiology 982
- Sensory Systems 673
- Cellular and Molecular Neuroscience 1.9k
- Pharmacology 1k
Countries citing papers authored by Stephen Alexander
This map shows the geographic impact of Stephen Alexander'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 Alexander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Alexander more than expected).
Fields of papers citing papers by Stephen Alexander
This network shows the impact of papers produced by Stephen Alexander. 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 Alexander. The network helps show where Stephen Alexander may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen Alexander, 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 258 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY Hit paper breakdown → | 2017 | 1570 |
| 2 | International Union of Basic and Clinical Pharmacology. LXXIX. Cannabinoid Receptors and Their Ligands: Beyond CB1 and CB2 Hit paper breakdown → | 2010 | 1396 |
| 3 | The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands Hit paper breakdown → | 2015 | 995 |
| 4 | ARRIVE 2.0 and the British Journal of Pharmacology: Updated guidance for 2020 Hit paper breakdown → | 2020 | 993 |
| 5 | The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands Hit paper breakdown → | 2013 | 801 |
| 6 | The Concise Guide to PHARMACOLOGY 2015/16: G protein‐coupled receptors Hit paper breakdown → | 2015 | 790 |
| 7 | Immunogenic structure of the influenza virus hemagglutinin Hit paper breakdown → | 1982 | 691 |
| 8 | THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: G protein‐coupled receptors Hit paper breakdown → | 2019 | 660 |
| 9 | endo-beta-N-acetylglucosaminidase F: endoglycosidase from Flavobacterium meningosepticum that cleaves both high-mannose and complex glycoproteins. Hit paper breakdown → | 1982 | 654 |
| 10 | THE CONCISE GUIDE TO PHARMACOLOGY 2017/18: Enzymes Hit paper breakdown → | 2017 | 588 |
| 11 | The Concise Guide to PHARMACOLOGY 2015/16: Enzymes Hit paper breakdown → | 2015 | 585 |
| 12 | THE CONCISE GUIDE TO PHARMACOLOGY 2017/18: G protein‐coupled receptors Hit paper breakdown → | 2017 | 561 |
| 13 | 2013 | 530 | |
| 14 | THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Enzymes Hit paper breakdown → | 2019 | 493 |
| 15 | 2008 | 487 | |
| 16 | THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: G protein‐coupled receptors Hit paper breakdown → | 2021 | 452 |
| 17 | The Concise Guide to PHARMACOLOGY 2013/14: Enzymes Hit paper breakdown → | 2013 | 414 |
| 18 | 1990 | 413 | |
| 19 | THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Introduction and Other Protein Targets Hit paper breakdown → | 2019 | 409 |
| 20 | The Concise Guide to PHARMACOLOGY 2023/24: Enzymes Hit paper breakdown → | 2023 | 370 |
About Stephen Alexander
Stephen Alexander is a scholar working on Physiology, Pharmacology, Molecular Biology, Computational Theory and Mathematics and Cellular and Molecular Neuroscience, having authored 258 papers that have together received 26.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (64 papers), Cannabis and Cannabinoid Research (43 papers), Computational Drug Discovery Methods (35 papers), Adenosine and Purinergic Signaling (28 papers), Ion channel regulation and function (21 papers), Neuroscience and Neuropharmacology Research (19 papers), Protein Kinase Regulation and GTPase Signaling (9 papers) and Pharmacogenetics and Drug Metabolism (9 papers). The work is most often cited by research in Pharmacology (4.1k citations), Physiology (982 citations), Sensory Systems (673 citations), Cellular and Molecular Neuroscience (1.9k citations) and Pharmacology (1k citations). Stephen Alexander has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Elena Faccenda, Adam J Pawson, Joanna L Sharman, John A. Peters, Christopher Southan, Jamie A. Davies, Eamonn Kelly, Helen E. Benson, Michael Spedding and Simon D Harding. Their work appears in journals such as British Journal of Pharmacology, Journal of Neurochemistry, Nucleic Acids Research, Pharmacological Reviews and The FASEB Journal.
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.