Matthew Gage
Impact in
- Virology top 10%
- HIV Research and Treatment
- Immunology top 10%
- Immune cells in cancer
Papers in
-
- Angiogenesis and VEGF in Cancer 4
- Metabolism, Diabetes, and Cancer 2
- Surgery 11
- Cholesterol and Lipid Metabolism 5
- Co-authors
- Inès Pineda‐Torra (10 shared papers)Óscar M. Pello (4 shared papers)Alba de Juan (1 shared paper)Mark T. Kearney (13 shared papers)Stephen B. Wheatcroft (13 shared papers)Richard M. Cubbon (12 shared papers)Hema Viswambharan (12 shared papers)Helen Imrie (11 shared papers)
- Journals
- Diabetes (5 papers)Endocrinology (3 papers)Journal of Proteome Research (2 papers)Atherosclerosis (2 papers)Heart (2 papers)
- Partner nations
- United KingdomUnited StatesSpain
In The Last Decade
Matthew Gage
32 papers receiving 963 citations
Peers
Comparison fields: 5 of 91
- Virology 64
- Immunology 259
- Endocrinology, Diabetes and Metabolism 146
- Cancer Research 118
- Physiology 186
Countries citing papers authored by Matthew Gage
This map shows the geographic impact of Matthew Gage'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 Matthew Gage with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Gage more than expected).
Fields of papers citing papers by Matthew Gage
This network shows the impact of papers produced by Matthew Gage. 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 Matthew Gage. The network helps show where Matthew Gage may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Gage, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 143 | |
| 2 | 2013 | 104 | |
| 3 | 2017 | 76 | |
| 4 | 2011 | 68 | |
| 5 | 2021 | 65 | |
| 6 | 2008 | 49 | |
| 7 | 2012 | 48 | |
| 8 | 2019 | 48 | |
| 9 | 2013 | 42 | |
| 10 | 2011 | 42 | |
| 11 | 2009 | 42 | |
| 12 | 2018 | 40 | |
| 13 | 2016 | 37 | |
| 14 | 2016 | 34 | |
| 15 | 2022 | 26 | |
| 16 | 2017 | 21 | |
| 17 | 2014 | 13 | |
| 18 | 2021 | 12 | |
| 19 | 2014 | 10 | |
| 20 | 2020 | 9 |
About Matthew Gage
Matthew Gage is a scholar working on Molecular Biology, Surgery, Immunology, Physiology and Cancer Research, having authored 32 papers that have together received 972 indexed citations. Recurring topics across this work include Nitric Oxide and Endothelin Effects (8 papers), Cholesterol and Lipid Metabolism (5 papers), Cancer, Lipids, and Metabolism (4 papers), Atherosclerosis and Cardiovascular Diseases (4 papers), Angiogenesis and VEGF in Cancer (4 papers), Immune cells in cancer (4 papers), Lipid metabolism and biosynthesis (3 papers) and Metabolism, Diabetes, and Cancer (2 papers). The work is most often cited by research in Virology (64 citations), Immunology (259 citations), Endocrinology, Diabetes and Metabolism (146 citations), Cancer Research (118 citations) and Physiology (186 citations). Matthew Gage has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Inès Pineda‐Torra, Óscar M. Pello, Alba de Juan, Mark T. Kearney, Stephen B. Wheatcroft, Richard M. Cubbon, Hema Viswambharan, Helen Imrie, Piruthivi Sukumar and Natalia Bécares. Their work appears in journals such as Diabetes, Endocrinology, Journal of Proteome Research, Atherosclerosis and Heart.
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.