Gary R. Mirams
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- Cardiac electrophysiology and arrhythmias 69
- Cardiac pacing and defibrillation studies 7
- Modeling and Simulation top 1%
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- Neuroscience and Neural Engineering 22
- Molecular Biology top 5%
- Ion channel regulation and function 40
- Receptor Mechanisms and Signaling 15
- Gene Regulatory Network Analysis 6
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- Probabilistic and Robust Engineering Design 7
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- Fault Detection and Control Systems 8
- Co-authors
- David J. GavaghanJonathan CooperPras PathmanathanYi CuiDenis NobleMichael ClerxAlexander G. FletcherChon Lok Lei
- Cited by
- Cardiology and Cardiovascular MedicineModeling and SimulationCellular and Molecular Neuroscience
- Journals
- Journal of Biological Chemistry (1 paper)Nature Communications (2 papers)Molecular Cell (1 paper)
- Partner nations
- United KingdomUnited StatesNetherlands
In The Last Decade
Gary R. Mirams
90 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 155
- Cardiology and Cardiovascular Medicine 1.8k
- Modeling and Simulation 225
- Cellular and Molecular Neuroscience 502
- Molecular Biology 1.7k
- Statistics, Probability and Uncertainty 178
Countries citing papers authored by Gary R. Mirams
This map shows the geographic impact of Gary R. Mirams'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 Gary R. Mirams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary R. Mirams more than expected).
Fields of papers citing papers by Gary R. Mirams
This network shows the impact of papers produced by Gary R. Mirams. 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 Gary R. Mirams. The network helps show where Gary R. Mirams may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gary R. Mirams, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 7 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 6 | |
| 11 | 2020 | 45 | |
| 12 | 2020 | 36 | |
| 13 | 2020 | 69 | |
| 14 | 2019 | 29 | |
| 15 | 2018 | 47 | |
| 16 | 2015 | 1 | |
| 17 | 2015 | 95 | |
| 18 | 2014 | 0 | |
| 19 | 2012 | 80 | |
| 20 | 2012 | 44 |
About Gary R. Mirams
Gary R. Mirams is a scholar working on Cardiology and Cardiovascular Medicine, Cellular and Molecular Neuroscience and Sensory Systems, having authored 96 papers that have together received 3.3k indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (69 papers), Ion channel regulation and function (40 papers), Neuroscience and Neural Engineering (22 papers), Receptor Mechanisms and Signaling (15 papers), Fault Detection and Control Systems (8 papers), Cardiac pacing and defibrillation studies (7 papers), Probabilistic and Robust Engineering Design (7 papers) and Gene Regulatory Network Analysis (6 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (1.8k citations), Modeling and Simulation (225 citations) and Cellular and Molecular Neuroscience (502 citations). Gary R. Mirams has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include David J. Gavaghan, Jonathan Cooper, Pras Pathmanathan, Yi Cui, Denis Noble, Michael Clerx, Alexander G. Fletcher, Chon Lok Lei, Helen M. Byrne and Joe Pitt‐Francis. Their work appears in journals such as Journal of Biological Chemistry, Nature Communications and Molecular 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.