Matthew Traylor
Impact in
Papers in
- Genetics 13
- Genetic Associations and Epidemiology 12
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- Bioinformatics and Genomic Networks 3
- Co-authors
- Hugh S. Markus (29 shared papers)Martin Dichgans (21 shared papers)Susanna C. Larsson (9 shared papers)Rainer Malik (10 shared papers)Cathie Sudlow (16 shared papers)Loes C.A. Rutten‐Jacobs (10 shared papers)Cathryn M. Lewis (16 shared papers)Hugh S. Markus (11 shared papers)
- Journals
- Stroke (15 papers)Neurology (4 papers)PLoS ONE (4 papers)Annals of Neurology (3 papers)Brain (3 papers)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Matthew Traylor
55 papers receiving 2.4k citations
Matthew Traylor's Hit Papers
Peers
Comparison fields: 5 of 103
- Neurology 246
- Neurology 339
- Genetics 496
- Rheumatology 224
- Cardiology and Cardiovascular Medicine 220
Countries citing papers authored by Matthew Traylor
This map shows the geographic impact of Matthew Traylor'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 Traylor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Traylor more than expected).
Fields of papers citing papers by Matthew Traylor
This network shows the impact of papers produced by Matthew Traylor. 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 Traylor. The network helps show where Matthew Traylor may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Traylor, 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 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 279 | |
| 2 | 2017 | 262 | |
| 3 | Genetic risk, incident stroke, and the benefits of adhering to a healthy lifestyle: cohort study of 306 473 UK Biobank participants Hit paper breakdown → | 2018 | 232 |
| 4 | 2019 | 176 | |
| 5 | 2018 | 134 | |
| 6 | 2020 | 117 | |
| 7 | 2018 | 91 | |
| 8 | 2017 | 83 | |
| 9 | 2022 | 71 | |
| 10 | 2019 | 64 | |
| 11 | 2019 | 59 | |
| 12 | 2018 | 58 | |
| 13 | 2018 | 55 | |
| 14 | 2017 | 52 | |
| 15 | 2016 | 50 | |
| 16 | 2016 | 46 | |
| 17 | 2019 | 43 | |
| 18 | 2021 | 34 | |
| 19 | 2019 | 34 | |
| 20 | 2018 | 33 |
About Matthew Traylor
Matthew Traylor is a scholar working on Genetics, Molecular Biology, Rheumatology, Neurology and Cardiology and Cardiovascular Medicine, having authored 55 papers that have together received 2.5k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (12 papers), Cerebrovascular and genetic disorders (5 papers), Folate and B Vitamins Research (4 papers), Renin-Angiotensin System Studies (3 papers), Bioinformatics and Genomic Networks (3 papers), Cancer-related molecular mechanisms research (3 papers), Moyamoya disease diagnosis and treatment (2 papers) and Bone health and osteoporosis research (2 papers). The work is most often cited by research in Neurology (246 citations), Neurology (339 citations), Genetics (496 citations), Rheumatology (224 citations) and Cardiology and Cardiovascular Medicine (220 citations). Matthew Traylor has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Hugh S. Markus, Martin Dichgans, Susanna C. Larsson, Rainer Malik, Cathie Sudlow, Loes C.A. Rutten‐Jacobs, Cathryn M. Lewis, Hugh S. Markus, Stephen Burgess and Kristiina Rannikmäe. Their work appears in journals such as Stroke, Neurology, PLoS ONE, Annals of Neurology and Brain.
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.