Chris Harbron
Impact in
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
- Health Informatics top 10%
Papers in
- Oncology 10
- PARP inhibition in cancer therapy 4
- Co-authors
- Mark Wappett (2 shared papers)Elizabeth A. Harrington (2 shared papers)Margaret H. Veldman-Jones (2 shared papers)Claire Rooney (1 shared paper)Alan Sharpe (1 shared paper)J. Carl Barrett (1 shared paper)Gayle Marshall (1 shared paper)Hollie Emery (1 shared paper)
- Journals
- Pharmaceutical Statistics (5 papers)Cancer Research (4 papers)Nature Medicine (2 papers)Mathematical Medicine and Biology A Journal of the IMA (2 papers)Nature Machine Intelligence (2 papers)
- Partner nations
- United KingdomSwitzerlandUnited States
In The Last Decade
Chris Harbron
38 papers receiving 887 citations
Peers
Comparison fields: 5 of 138
- Statistics and Probability 122
- Health Informatics 18
- Cancer Research 150
- Oncology 195
- Pathology and Forensic Medicine 123
Countries citing papers authored by Chris Harbron
This map shows the geographic impact of Chris Harbron'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 Chris Harbron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Harbron more than expected).
Fields of papers citing papers by Chris Harbron
This network shows the impact of papers produced by Chris Harbron. 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 Chris Harbron. The network helps show where Chris Harbron may publish in the future.
Co-authors
The 25 scholars most cited alongside Chris Harbron, 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 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 234 | |
| 2 | 2011 | 67 | |
| 3 | 2014 | 54 | |
| 4 | 2021 | 47 | |
| 5 | 2017 | 44 | |
| 6 | 2021 | 40 | |
| 7 | 2012 | 34 | |
| 8 | 2007 | 33 | |
| 9 | 2011 | 31 | |
| 10 | 2023 | 30 | |
| 11 | 2016 | 28 | |
| 12 | 2010 | 26 | |
| 13 | 2020 | 24 | |
| 14 | 2014 | 23 | |
| 15 | 2022 | 21 | |
| 16 | 2023 | 21 | |
| 17 | 2013 | 20 | |
| 18 | 2019 | 20 | |
| 19 | 2016 | 15 | |
| 20 | 2022 | 14 |
About Chris Harbron
Chris Harbron is a scholar working on Oncology, Molecular Biology, Computational Theory and Mathematics, Statistics and Probability and Pathology and Forensic Medicine, having authored 41 papers that have together received 908 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (8 papers), Lymphoma Diagnosis and Treatment (6 papers), Computational Drug Discovery Methods (6 papers), Chronic Lymphocytic Leukemia Research (5 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), PARP inhibition in cancer therapy (4 papers) and BRCA gene mutations in cancer (3 papers). The work is most often cited by research in Statistics and Probability (122 citations), Health Informatics (18 citations), Cancer Research (150 citations), Oncology (195 citations) and Pathology and Forensic Medicine (123 citations). Chris Harbron has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Mark Wappett, Elizabeth A. Harrington, Margaret H. Veldman-Jones, Claire Rooney, Alan Sharpe, J. Carl Barrett, Gayle Marshall, Hollie Emery, Roz Brant and Michael Dymond. Their work appears in journals such as Pharmaceutical Statistics, Cancer Research, Nature Medicine, Mathematical Medicine and Biology A Journal of the IMA and Nature Machine Intelligence.
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.