Dave Bower
Impact in
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- Quality and Safety in Healthcare
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- Computational Drug Discovery Methods
Papers in
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- Animal testing and alternatives 2
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- Computational Drug Discovery Methods 2
- Co-authors
- Martin McKee (1 shared paper)John Cairns (1 shared paper)John Brebner (1 shared paper)Adrian Grant (1 shared paper)G Mowatt (1 shared paper)Catrin Hasselgren (1 shared paper)Kevin P. Cross (4 shared papers)Kevin M. Crofton (1 shared paper)
- Journals
- Toxicology Letters (1 paper)SAR and QSAR in environmental research (1 paper)International Journal of Technology Assessment in Health Care (1 paper)Trends in biotechnology (1 paper)Computational Toxicology (2 papers)
- Partner nations
- United KingdomItalyDemocratic Republic of the Congo
In The Last Decade
Dave Bower
5 papers receiving 32 citations
Peers
Comparison fields: 5 of 35
- Medical Laboratory Technology 2
- Computational Theory and Mathematics 7
- Health, Toxicology and Mutagenesis 6
- Economics and Econometrics 10
- Statistics, Probability and Uncertainty 2
Countries citing papers authored by Dave Bower
This map shows the geographic impact of Dave Bower'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 Dave Bower with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dave Bower more than expected).
Fields of papers citing papers by Dave Bower
This network shows the impact of papers produced by Dave Bower. 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 Dave Bower. The network helps show where Dave Bower may publish in the future.
Co-authors
The 19 scholars most cited alongside Dave Bower, 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 | 1998 | 17 | |
| 2 | 2021 | 8 | |
| 3 | 1989 | 4 | |
| 4 | 2021 | 3 | |
| 5 | 2013 | 1 | |
| 6 | 2015 | 0 |
About Dave Bower
Dave Bower is a scholar working on Small Animals, Computational Theory and Mathematics, Cardiology and Cardiovascular Medicine, General Health Professions and Health, Toxicology and Mutagenesis, having authored 6 papers that have together received 33 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (2 papers), Animal testing and alternatives (2 papers), Cardiac electrophysiology and arrhythmias (1 paper), Effects and risks of endocrine disrupting chemicals (1 paper), Health Systems, Economic Evaluations, Quality of Life (1 paper), Healthcare cost, quality, practices (1 paper), Pharmaceutical Economics and Policy (1 paper) and Risk and Safety Analysis (1 paper). The work is most often cited by research in Medical Laboratory Technology (2 citations), Computational Theory and Mathematics (7 citations), Health, Toxicology and Mutagenesis (6 citations), Economics and Econometrics (10 citations) and Statistics, Probability and Uncertainty (2 citations). Dave Bower has collaborated with scholars based in United Kingdom, Italy and Democratic Republic of the Congo. Frequent co-authors include Martin McKee, John Cairns, John Brebner, Adrian Grant, G Mowatt, Catrin Hasselgren, Kevin P. Cross, Kevin M. Crofton, Craig Zwickl and Arianna Bassan. Their work appears in journals such as Toxicology Letters, SAR and QSAR in environmental research, International Journal of Technology Assessment in Health Care, Trends in biotechnology and Computational Toxicology.
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.