Paul Leff
- Physiology top 0.5%
- Adenosine and Purinergic Signaling 3
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- Neuropeptides and Animal Physiology 6
- Molecular Biology top 5%
- Receptor Mechanisms and Signaling 12
- Protein Structure and Dynamics 3
- Chemical Synthesis and Analysis 2
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- Analytical Chemistry and Chromatography 4
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- Hemoglobin structure and function 4
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- Computational Drug Discovery Methods 3
- Co-authors
- Ian DaintyStephen E. O'ConnorIain G. DougallJoseph GoldfarbKelly A. BergSaul MaayaniWilliam P. ClarkeRichard A. Bond
- Journals
- Trends in Pharmacological Sciences (10 papers)Biochemical Journal (2 papers)European Journal of Biochemistry (1 paper)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Paul Leff
26 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Physiology 446
- Cellular and Molecular Neuroscience 1.2k
- Molecular Biology 1.8k
- Endocrine and Autonomic Systems 145
- Cardiology and Cardiovascular Medicine 304
Countries citing papers authored by Paul Leff
This map shows the geographic impact of Paul Leff'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 Paul Leff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Leff more than expected).
Fields of papers citing papers by Paul Leff
This network shows the impact of papers produced by Paul Leff. 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 Paul Leff. The network helps show where Paul Leff may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Paul Leff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 28 | |
| 2 | 2002 | 5 | |
| 3 | 2000 | 7 | |
| 4 | 1998 | 438 | |
| 5 | 1997 | 12 | |
| 6 | 1997 | 169 | |
| 7 | 1996 | 10 | |
| 8 | 1996 | 18 | |
| 9 | 1996 | 12 | |
| 10 | 1995 | 69 | |
| 11 | Physiological effects of inverse agonists in transgenic mice with myocardial overexpression of the β2-adrenoceptorbreakdown → | 1995 | 366 |
| 12 | 1995 | 424 | |
| 13 | 1994 | 62 | |
| 14 | 1993 | 156 | |
| 15 | 1991 | 317 | |
| 16 | 1990 | 25 | |
| 17 | 1987 | 8 | |
| 18 | 1981 | 13 | |
| 19 | 1980 | 65 | |
| 20 | 1977 | 1 |
About Paul Leff
Paul Leff is a scholar working on Physiology, Cellular and Molecular Neuroscience, Spectroscopy, Molecular Biology and Cell Biology, having authored 26 papers that have together received 2.6k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (12 papers), Neuropeptides and Animal Physiology (6 papers), Analytical Chemistry and Chromatography (4 papers), Hemoglobin structure and function (4 papers), Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers), Adenosine and Purinergic Signaling (3 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Physiology (446 citations), Cellular and Molecular Neuroscience (1.2k citations), Molecular Biology (1.8k citations), Endocrine and Autonomic Systems (145 citations) and Cardiology and Cardiovascular Medicine (304 citations). Paul Leff has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Ian Dainty, Stephen E. O'Connor, Iain G. Dougall, Joseph Goldfarb, Kelly A. Berg, Saul Maayani, William P. Clarke, Richard A. Bond, William G. Bardsley and Robert J. Lefkowitz. Their work appears in journals such as Trends in Pharmacological Sciences, Biochemical Journal, European Journal of Biochemistry, Current Opinion in Pharmacology and Nature.
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.