Daniel P. Russo
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Health Informatics top 5%
Papers in
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- Computational Drug Discovery Methods 30
-
- Animal testing and alternatives 7
- Co-authors
- Sean Ekins (7 shared papers)Hao Zhu (25 shared papers)Kimberley M. Zorn (6 shared papers)Alex M. Clark (5 shared papers)Alexandru V. Korotcov (2 shared papers)Valery Tkachenko (2 shared papers)Thomas R. Lane (4 shared papers)Anthony James Hickey (1 shared paper)
- Journals
- Environmental Science & Technology (6 papers)Molecular Pharmaceutics (4 papers)Environmental Health Perspectives (2 papers)American Journal of Otolaryngology (2 papers)ACS Sustainable Chemistry & Engineering (2 papers)
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Daniel P. Russo
40 papers receiving 1.9k citations
Daniel P. Russo's Hit Papers
Peers
Comparison fields: 5 of 155
- Computational Theory and Mathematics 921
- Health Informatics 39
- Small Animals 119
- Biophysics 85
- Pharmacology 122
Countries citing papers authored by Daniel P. Russo
This map shows the geographic impact of Daniel P. Russo'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 Daniel P. Russo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel P. Russo more than expected).
Fields of papers citing papers by Daniel P. Russo
This network shows the impact of papers produced by Daniel P. Russo. 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 Daniel P. Russo. The network helps show where Daniel P. Russo may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel P. Russo, 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 | Exploiting machine learning for end-to-end drug discovery and development Hit paper breakdown → | 2019 | 429 |
| 2 | 2017 | 275 | |
| 3 | 2018 | 134 | |
| 4 | 2021 | 110 | |
| 5 | 2018 | 92 | |
| 6 | 2017 | 92 | |
| 7 | 2019 | 70 | |
| 8 | 2019 | 53 | |
| 9 | 2020 | 52 | |
| 10 | 2021 | 50 | |
| 11 | 2020 | 48 | |
| 12 | 2020 | 45 | |
| 13 | 2022 | 37 | |
| 14 | 2021 | 34 | |
| 15 | 2022 | 33 | |
| 16 | 2020 | 31 | |
| 17 | 2021 | 31 | |
| 18 | 2023 | 28 | |
| 19 | 2021 | 28 | |
| 20 | 2016 | 27 |
About Daniel P. Russo
Daniel P. Russo is a scholar working on Computational Theory and Mathematics, Small Animals, Pharmacology, Molecular Biology and Biophysics, having authored 41 papers that have together received 1.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (30 papers), Animal testing and alternatives (7 papers), Metabolomics and Mass Spectrometry Studies (6 papers), Pharmacogenetics and Drug Metabolism (6 papers), Machine Learning in Materials Science (5 papers), Estrogen and related hormone effects (3 papers), Cell Image Analysis Techniques (3 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). The work is most often cited by research in Computational Theory and Mathematics (921 citations), Health Informatics (39 citations), Small Animals (119 citations), Biophysics (85 citations) and Pharmacology (122 citations). Daniel P. Russo has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Sean Ekins, Hao Zhu, Kimberley M. Zorn, Alex M. Clark, Alexandru V. Korotcov, Valery Tkachenko, Thomas R. Lane, Anthony James Hickey, Jennifer J. Klein and Ana C. Puhl. Their work appears in journals such as Environmental Science & Technology, Molecular Pharmaceutics, Environmental Health Perspectives, American Journal of Otolaryngology and ACS Sustainable Chemistry & Engineering.
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.