Tim Peakman
- Genetics top 0.5%
- Genetic Associations and Epidemiology 3
- Genomics and Rare Diseases 1
- Physiology top 1%
- Biomedical Ethics and Regulation 1
- Geriatrics and Gerontology top 2%
- Health Informatics top 2%
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- Biotechnology and Related Fields 2
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- Computational Drug Discovery Methods 2
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- Health Systems, Economic Evaluations, Quality of Life 2
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- Health, Environment, Cognitive Aging 2
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- Medical Imaging Techniques and Applications 1
Tim Peakman
15 papers receiving 8.4k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Genetics 2.2k
- Physiology 1.7k
- Geriatrics and Gerontology 205
- Health Informatics 67
- Public Health, Environmental and Occupational Health 1.4k
Countries citing papers authored by Tim Peakman
This map shows the geographic impact of Tim Peakman'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 Tim Peakman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Peakman more than expected).
Fields of papers citing papers by Tim Peakman
This network shows the impact of papers produced by Tim Peakman. 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 Tim Peakman. The network helps show where Tim Peakman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tim Peakman, 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 | 2017 | 49 | |
| 2 | Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Studybreakdown → | 2017 | 790 |
| 3 | UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Agebreakdown → | 2015 | 6888 |
| 4 | 2014 | 11 | |
| 5 | 2014 | 19 | |
| 6 | 2013 | 160 | |
| 7 | 2012 | 26 | |
| 8 | 2012 | 350 | |
| 9 | 2008 | 19 | |
| 10 | 2005 | 165 | |
| 11 | 2003 | 17 | |
| 12 | 2001 | 1 | |
| 13 | 2000 | 2 | |
| 14 | 1999 | 5 | |
| 15 | 1989 | 9 |
About Tim Peakman
Tim Peakman is a scholar working on Periodontics, Public Health, Environmental and Occupational Health, Physiology, Health, Toxicology and Mutagenesis and Management of Technology and Innovation, having authored 15 papers that have together received 8.5k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (3 papers), Computational Drug Discovery Methods (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Biotechnology and Related Fields (2 papers), Health, Environment, Cognitive Aging (2 papers), Genomics and Rare Diseases (1 paper), Biomedical Ethics and Regulation (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Genetics (2.2k citations), Physiology (1.7k citations), Geriatrics and Gerontology (205 citations), Health Informatics (67 citations) and Public Health, Environmental and Occupational Health (1.4k citations). Tim Peakman has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Tim Sprosen, Rory Collins, Paul M. Matthews, Paul Downey, Cathie Sudlow, John Danesh, Paul Elliott, Jill P. Pell, Naomi E. Allen and John Gallacher. Their work appears in journals such as Drug Discovery Today, International Journal of Epidemiology, Pharmacogenomics, BMC Genomics and PLoS Medicine.
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.