Tim Peakman

16.3k total citations · 2 hit papers
15 papers, 8.5k citations indexed

About

Tim Peakman is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology and Physiology. According to data from OpenAlex, Tim Peakman has authored 15 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Public Health, Environmental and Occupational Health, 4 papers in Molecular Biology and 4 papers in Physiology. Recurrent topics in Tim Peakman's work include Genetic Associations and Epidemiology (3 papers), Computational Drug Discovery Methods (2 papers) and Health Systems, Economic Evaluations, Quality of Life (2 papers). Tim Peakman is often cited by papers focused on Genetic Associations and Epidemiology (3 papers), Computational Drug Discovery Methods (2 papers) and Health Systems, Economic Evaluations, Quality of Life (2 papers). Tim Peakman collaborates with scholars based in United Kingdom, Canada and United States. Tim Peakman's co-authors include Tim Sprosen, Rory Collins, Paul M. Matthews, Cathie Sudlow, Jill P. Pell, Paul Downey, John Gallacher, John Danesh, Naomi E. Allen and Paul Elliott and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Annals of the New York Academy of Sciences.

In The Last Decade

Tim Peakman

15 papers receiving 8.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

2015 6.9k citations Cathie Sudlow, John Gallacher et al. PLoS Medicine profile →
Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study

2017 790 citations Aiden Doherty, Dan Jackson et al. PLoS ONE profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tim Peakman United Kingdom	11	2.2k	1.7k	1.4k	1.3k	1.1k	15	8.5k
Tim Sprosen United Kingdom	6	2.7k 1.2×	1.6k 1.0×	1.5k 1.1×	1.4k 1.1×	1.2k 1.1×	6	9.8k
Paul Downey Ireland	18	2.1k 1.0×	1.2k 0.7×	1.3k 0.9×	1.3k 1.0×	954 0.9×	65	8.2k
Giok Ong United Kingdom	9	2.0k 0.9×	1.2k 0.7×	1.0k 0.7×	1.1k 0.9×	895 0.8×	9	7.2k
Martin Landray United Kingdom	37	2.1k 1.0×	1.4k 0.8×	1.3k 0.9×	1.4k 1.1×	2.1k 2.0×	124	11.4k
Jane Green United Kingdom	46	2.9k 1.3×	2.1k 1.2×	1.9k 1.3×	2.2k 1.8×	1.5k 1.4×	125	14.1k
Harold Snieder Netherlands	65	3.1k 1.4×	1.6k 0.9×	1.7k 1.2×	2.9k 2.3×	3.2k 3.0×	404	15.4k
Gerard J. Blauw Netherlands	48	917 0.4×	2.3k 1.3×	796 0.6×	2.0k 1.6×	2.0k 1.9×	177	11.8k
Clifford Qualls United States	51	720 0.3×	2.0k 1.1×	1.3k 0.9×	1.0k 0.8×	583 0.6×	296	11.6k
Cosetta Minelli United Kingdom	41	3.1k 1.4×	1.2k 0.7×	690 0.5×	1.8k 1.4×	607 0.6×	130	9.3k
Michael V. Holmes United Kingdom	41	3.5k 1.6×	1.6k 0.9×	1.1k 0.8×	2.5k 2.0×	1.2k 1.2×	137	10.9k

Countries citing papers authored by Tim Peakman

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Tim Peakman

This figure shows the co-authorship network connecting the top 25 collaborators of Tim Peakman. A scholar is included among the top collaborators of Tim Peakman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tim Peakman. Tim Peakman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Doherty, Aiden, Dan Jackson, Nils Hammerla, et al.. (2017). Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS ONE. 12(2). e0169649–e0169649. 790 indexed citations breakdown →

Welsh, Samantha, Tim Peakman, Simon Sheard, & Rachael Almond. (2017). Comparison of DNA quantification methodology used in the DNA extraction protocol for the UK Biobank cohort. BMC Genomics. 18(1). 26–26. 49 indexed citations

Sudlow, Cathie, John Gallacher, Naomi E. Allen, et al.. (2015). UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age. PLoS Medicine. 12(3). e1001779–e1001779. 6888 indexed citations breakdown →

Gaye, Amadou, Tim Peakman, Martin D. Tobin, & Paul R. Burton. (2014). Understanding the impact of pre-analytic variation in haematological and clinical chemistry analytes on the power of association studies. International Journal of Epidemiology. 43(5). 1633–1644. 11 indexed citations

Vaught, Jim, Abraham Ayodeji Abayomi, Tim Peakman, et al.. (2014). Critical Issues in International Biobanking. Clinical Chemistry. 60(11). 1368–1374. 19 indexed citations

Petersen, Steffen E., Paul M. Matthews, Fabian Bamberg, et al.. (2013). Imaging in population science: cardiovascular magnetic resonance in 100,000 participants of UK Biobank - rationale, challenges and approaches. Journal of Cardiovascular Magnetic Resonance. 15(1). 46–46. 160 indexed citations

Pramanik, Rashida, H. H. Thompson, James O. Kistler, et al.. (2012). Effects of the UK Biobank collection protocol on potential biomarkers in saliva. International Journal of Epidemiology. 41(6). 1786–1797. 26 indexed citations

Allen, Naomi E., Cathie Sudlow, Paul Downey, et al.. (2012). UK Biobank: Current status and what it means for epidemiology. Health Policy and Technology. 1(3). 123–126. 350 indexed citations

Salway, Fiona, Phillip Day, W E Ollier, & Tim Peakman. (2008). Levels of 5′ RNA tags in plasma and buffy coat from EDTA blood increase with time. International Journal of Epidemiology. 37(suppl_1). i11–i15. 19 indexed citations

10.

Ollier, William, Tim Sprosen, & Tim Peakman. (2005). UK Biobank: From Concept to Reality. Pharmacogenomics. 6(6). 639–646. 165 indexed citations

11.

Peakman, Tim, et al.. (2003). Delivering the power of discovery in large pharmaceutical organizations. Drug Discovery Today. 8(5). 203–211. 17 indexed citations

12.

Peakman, Tim, et al.. (2001). Assessing the impact of current trends in genomics on the future of pharmaceutical R&D. Drug Discovery Today. 6(4). 161–162. 1 indexed citations

13.

Peakman, Tim. (2000). Steering a course through the technology maze. Drug Discovery Today. 5(8). 337–343. 2 indexed citations

14.

Clare, Jeff J., et al.. (1999). Cloning and Functional Analysis of the Type III Na⁺ Channel from Human Brain. Annals of the New York Academy of Sciences. 868(1). 80–83. 5 indexed citations

15.

Peakman, Tim, Martin Pagé, & Dirk R. Gewert. (1989). Increased recombinational efficiency in insect cells irradiated with snort wavelength ultra-violet light. Nucleic Acids Research. 17(13). 5403–5403. 9 indexed citations

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.

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