Christopher G. Tate
- Cellular and Molecular Neuroscience top 0.1%
- Neuropeptides and Animal Physiology 44
- Physiology top 0.1%
- Adenosine and Purinergic Signaling 12
- Molecular Biology top 0.2%
- Receptor Mechanisms and Signaling 87
- Lipid Membrane Structure and Behavior 16
- Protein Structure and Dynamics 11
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- Monoclonal and Polyclonal Antibodies Research 24
- Structural Biology top 2%
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- Mass Spectrometry Techniques and Applications 12
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- Drug Transport and Resistance Mechanisms 10
- Co-authors
- Tony WarneGebhard F. X. SchertlerPatricia C. EdwardsAndrew G. W. LeslieGuillaume LebonMaría J. Serrano‐VegaReinhard GrisshammerByron Carpenter
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Christopher G. Tate
127 papers receiving 13.1k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Cellular and Molecular Neuroscience 5.7k
- Physiology 1.1k
- Molecular Biology 11.7k
- Radiology, Nuclear Medicine and Imaging 2.2k
- Structural Biology 111
Countries citing papers authored by Christopher G. Tate
This map shows the geographic impact of Christopher G. Tate'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 Christopher G. Tate with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher G. Tate more than expected).
Fields of papers citing papers by Christopher G. Tate
This network shows the impact of papers produced by Christopher G. Tate. 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 Christopher G. Tate. The network helps show where Christopher G. Tate may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Christopher G. Tate, 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 | 2026 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 15 | |
| 4 | 2024 | 3 | |
| 5 | 2021 | 14 | |
| 6 | 2020 | 1 | |
| 7 | 2020 | 59 | |
| 8 | 2019 | 85 | |
| 9 | 2018 | 52 | |
| 10 | 2017 | 21 | |
| 11 | 2017 | 13 | |
| 12 | 2017 | 200 | |
| 13 | Structure of the adenosine A(2A) receptor bound to an engineered G protein (vol 536, pg 104, 2016) | 2016 | 7 |
| 14 | 2015 | 277 | |
| 15 | 2014 | 42 | |
| 16 | 2013 | 123 | |
| 17 | 2013 | 18 | |
| 18 | 2011 | 453 | |
| 19 | 2010 | 94 | |
| 20 | 2003 | 109 |
About Christopher G. Tate
Christopher G. Tate is a scholar working on Cellular and Molecular Neuroscience, Physiology and Molecular Biology, having authored 130 papers that have together received 13.4k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (87 papers), Neuropeptides and Animal Physiology (44 papers), Monoclonal and Polyclonal Antibodies Research (24 papers), Lipid Membrane Structure and Behavior (16 papers), Mass Spectrometry Techniques and Applications (12 papers), Adenosine and Purinergic Signaling (12 papers), Protein Structure and Dynamics (11 papers) and Drug Transport and Resistance Mechanisms (10 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (5.7k citations), Physiology (1.1k citations) and Molecular Biology (11.7k citations). Christopher G. Tate has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Tony Warne, Gebhard F. X. Schertler, Patricia C. Edwards, Andrew G. W. Leslie, Guillaume Lebon, María J. Serrano‐Vega, Reinhard Grisshammer, Byron Carpenter, Rony Nehmé and AJ Venkatakrishnan. Their work appears in journals such as Nature, Science and Cell.
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.