Greg T. Sutherland
- Developmental Neuroscience top 2%
- Neurology top 2%
- Neuroinflammation and Neurodegeneration Mechanisms 15
- Parkinson's Disease Mechanisms and Treatments 12
- Neurological Disease Mechanisms and Treatments 7
- Neurological diseases and metabolism 6
- Biological Psychiatry top 5%
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- Nuclear Receptors and Signaling 7
- Physiology top 5%
- Alzheimer's disease research and treatments 26
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- Dementia and Cognitive Impairment Research 9
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- Metabolomics and Mass Spectrometry Studies 6
- Co-authors
- Jillian J. KrilDonna SheedyClaude V. DennisBelal ChamiMichael RodriguezGeorge D. MellickPeter A. SilburnPaul K. Witting
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Greg T. Sutherland
72 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 146
- Developmental Neuroscience 223
- Neurology 403
- Biological Psychiatry 97
- Cellular and Molecular Neuroscience 393
- Physiology 486
Countries citing papers authored by Greg T. Sutherland
This map shows the geographic impact of Greg T. Sutherland'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 Greg T. Sutherland with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg T. Sutherland more than expected).
Fields of papers citing papers by Greg T. Sutherland
This network shows the impact of papers produced by Greg T. Sutherland. 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 Greg T. Sutherland. The network helps show where Greg T. Sutherland may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Greg T. Sutherland, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 14 | |
| 9 | 2023 | 15 | |
| 10 | 2023 | 19 | |
| 11 | 2022 | 11 | |
| 12 | 2022 | 7 | |
| 13 | 2021 | 6 | |
| 14 | 2021 | 36 | |
| 15 | 2021 | 17 | |
| 16 | 2020 | 11 | |
| 17 | 2019 | 46 | |
| 18 | 2018 | 2 | |
| 19 | 2010 | 50 | |
| 20 | 2005 | 19 |
About Greg T. Sutherland
Greg T. Sutherland is a scholar working on Neurology, Neurology, Physiology, Cellular and Molecular Neuroscience and Developmental Neuroscience, having authored 80 papers that have together received 2.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (26 papers), Neuroinflammation and Neurodegeneration Mechanisms (15 papers), Parkinson's Disease Mechanisms and Treatments (12 papers), Dementia and Cognitive Impairment Research (9 papers), Neurological Disease Mechanisms and Treatments (7 papers), Nuclear Receptors and Signaling (7 papers), Metabolomics and Mass Spectrometry Studies (6 papers) and Neurological diseases and metabolism (6 papers). The work is most often cited by research in Developmental Neuroscience (223 citations), Neurology (403 citations), Biological Psychiatry (97 citations), Cellular and Molecular Neuroscience (393 citations) and Physiology (486 citations). Greg T. Sutherland has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Jillian J. Kril, Donna Sheedy, Claude V. Dennis, Belal Chami, Michael Rodriguez, George D. Mellick, Peter A. Silburn, Paul K. Witting, Graham Ramsay and J N Baxter. Their work appears in journals such as Alcohol, Scientific Reports, Journal of Alzheimer s Disease, PLoS ONE and Movement Disorders.
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.