Sean Ekins

22.6k citations
383 papers · 15.6k indexed · 3 hit papers · h-index 69

Impact in

Papers in

Sean Ekins

369 papers receiving 15.1k citations

Hit Papers

Dual use of artificial-intelligence-powered drug discovery 2022 · 162 citations
1622007202620132019100200300400

Peers

Sean Ekins
Comparison fields: 5 of 202
  • Pharmacology 3.9k
  • Computational Theory and Mathematics 6.3k
  • Infectious Diseases 2.1k
  • Oncology 2.5k
  • Molecular Biology 6.1k
Replace Tudor I. Oprea with:
Tudor I. Oprea United States
Hualiang Jiang China
Tingjun Hou China
Alexander Tropsha United States
Feixiong Cheng United States
Yu Chen China
Olivier Michielin Switzerland
Jürgen Bajorath Germany
Yun Tang China
Gisbert Schneider Switzerland
Sean Ekins relative to Tudor I. Oprea United States Tudor I. Oprea's profile →
Citations per field
00.5×2.9×
Tudor I. Oprea · 1×
Citations per year

Countries citing papers authored by Sean Ekins

Since Specialization
Citations

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

Fields of papers citing papers by Sean Ekins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sean Ekins, 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 Sean Ekins Line = papers co-authored together Sean Ekins links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20235
3 20232
4 20233
5 20216
6 202029
7 202017
8
Exploiting machine learning for end-to-end drug discovery and development
Hit paper breakdown →
2019352
9 201826
10 201848
11 201530
12 201511
13 20145
14 20132
15 201332
16 201332
17 201068
18 201057
19 200892
20
Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals (Wiley Series on Technologies for the Pharmaceutical Industry)
20072

About Sean Ekins

Sean Ekins is a scholar working on Pharmacology, Computational Theory and Mathematics, Infectious Diseases, Oncology and Molecular Biology, having authored 383 papers that have together received 15.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (170 papers), Pharmacogenetics and Drug Metabolism (95 papers), Drug Transport and Resistance Mechanisms (53 papers), Tuberculosis Research and Epidemiology (45 papers), Analytical Chemistry and Chromatography (31 papers), Estrogen and related hormone effects (23 papers), HIV/AIDS drug development and treatment (18 papers) and Bioinformatics and Genomic Networks (18 papers). The work is most often cited by research in Pharmacology (3.9k citations), Computational Theory and Mathematics (6.3k citations), Infectious Diseases (2.1k citations), Oncology (2.5k citations) and Molecular Biology (6.1k citations). Sean Ekins has collaborated with scholars based in United States, United Kingdom and Brazil. Frequent co-authors include Steven Wrighton, Antony Williams, Matthew D. Krasowski, Peter W. Swaan, Bernard Testa, Jordi Mestres, Alex M. Clark, Joel S. Freundlich, Kimberley M. Zorn and James H. Wikel. Their work appears in journals such as Pharmaceutical Research, Drug Metabolism and Disposition, Drug Discovery Today, Journal of Chemical Information and Modeling and Molecular Pharmaceutics.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026