Stephen Fowler

1.6k citations
47 papers · 1.1k indexed · h-index 22

Stephen Fowler

47 papers receiving 1.1k citations

Peers

Stephen Fowler
Comparison fields: 5 of 90
  • Pharmacology 560
  • Oncology 314
  • Computational Theory and Mathematics 149
  • Hepatology 55
  • Pediatrics, Perinatology and Child Health 111
Replace Upendra A. Argikar with:
Upendra A. Argikar United States
David B. Duignan United States
Ken Grime United Kingdom
Jasminder Sahi United States
Hayley S. Brown United Kingdom
Donald Tweedie United States
Jane R. Kenny United States
Jouko Uusitalo Finland
Kenneth J. Ruterbories United States
Ronald de Vries Belgium
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Citations per field
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Upendra A. Argikar · 1×
Citations per year

Countries citing papers authored by Stephen Fowler

Since Specialization
Citations

This map shows the geographic impact of Stephen Fowler'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 Stephen Fowler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Fowler more than expected).

Fields of papers citing papers by Stephen Fowler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen Fowler. 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 Stephen Fowler. The network helps show where Stephen Fowler may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Stephen Fowler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stephen Fowler Line = papers co-authored together Stephen Fowler links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20245
2 20241
3 20239
4 20237
5 202110
6 202112
7 202078
8 202028
9 201910
10 201912
11 201829
12 201833
13 201788
14 201625
15 201511
16 20154
17 201447
18 201421
19 201227
20 200924

About Stephen Fowler

Stephen Fowler is a scholar working on Pharmacology, Oncology, Transplantation, Biological Psychiatry and Pediatrics, Perinatology and Child Health, having authored 47 papers that have together received 1.1k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (38 papers), Drug Transport and Resistance Mechanisms (22 papers), 3D Printing in Biomedical Research (4 papers), Neonatal Health and Biochemistry (3 papers), Lung Cancer Treatments and Mutations (3 papers), Computational Drug Discovery Methods (3 papers), Liver Disease Diagnosis and Treatment (3 papers) and Drug-Induced Hepatotoxicity and Protection (3 papers). The work is most often cited by research in Pharmacology (560 citations), Oncology (314 citations), Computational Theory and Mathematics (149 citations), Hepatology (55 citations) and Pediatrics, Perinatology and Child Health (111 citations). Stephen Fowler has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Neil Parrott, Hongjian Zhang, Justine Badée, Michael Gertz, Stephan Schmidt, Abby C. Collier, Olaf Kuhlmann, Kenichi Umehara, Michael Derks and Christoph Funk. Their work appears in journals such as Drug Metabolism and Disposition, The AAPS Journal, Xenobiotica, Lab on a Chip and Clinical Pharmacokinetics.

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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