Jeff Blaney
Impact in
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- Computational Drug Discovery Methods
- Health Informatics top 5%
Papers in ⓘ
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- Computational Drug Discovery Methods 5
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- Genetics, Bioinformatics, and Biomedical Research 1
- Biochemical and Molecular Research 1
- Co-authors
- Matthias Zentgraf (1 shared paper)Alleyn T. Plowright (1 shared paper)John E. Hill (1 shared paper)Matthias Köhler (1 shared paper)Norman Sieroka (1 shared paper)Robert A. Goodnow (1 shared paper)José S. Duca (1 shared paper)Johanna M. Jansen (1 shared paper)
- Journals
- Journal of Computer-Aided Molecular Design (2 papers)Bioorganic & Medicinal Chemistry Letters (2 papers)Molecular Cancer Therapeutics (1 paper)Nature Reviews Drug Discovery (1 paper)Journal of Medicinal Chemistry (1 paper)
- Partner nations
- United StatesFranceUnited Kingdom
In The Last Decade
Jeff Blaney
8 papers receiving 648 citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Computational Theory and Mathematics 392
- Health Informatics 23
- Biophysics 32
- Molecular Biology 342
- Materials Chemistry 179
Countries citing papers authored by Jeff Blaney
This map shows the geographic impact of Jeff Blaney'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 Jeff Blaney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Blaney more than expected).
Fields of papers citing papers by Jeff Blaney
This network shows the impact of papers produced by Jeff Blaney. 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 Jeff Blaney. The network helps show where Jeff Blaney may publish in the future.
Co-authors
The 25 scholars most cited alongside Jeff Blaney, 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 | Rethinking drug design in the artificial intelligence era Hit paper breakdown → | 2019 | 496 |
| 2 | 2017 | 67 | |
| 3 | 2008 | 52 | |
| 4 | 2011 | 29 | |
| 5 | 2015 | 14 | |
| 6 | 2015 | 13 | |
| 7 | Selective inhibition of MET protein receptor tyrosine kinase by SGX523 | 2007 | 6 |
| 8 | 2012 | 3 | |
| 9 | 2025 | 0 | |
| 10 | New problems that should be addressed in the next ten years 7 | 1999 | 0 |
About Jeff Blaney
Jeff Blaney is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Pharmacology and Hepatology, having authored 10 papers that have together received 680 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Genetics, Bioinformatics, and Biomedical Research (1 paper), Design Education and Practice (1 paper), Quinazolinone synthesis and applications (1 paper), Cancer, Hypoxia, and Metabolism (1 paper) and Biochemical and Molecular Research (1 paper). The work is most often cited by research in Computational Theory and Mathematics (392 citations), Health Informatics (23 citations), Biophysics (32 citations), Molecular Biology (342 citations) and Materials Chemistry (179 citations). Jeff Blaney has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Matthias Zentgraf, Alleyn T. Plowright, John E. Hill, Matthias Köhler, Norman Sieroka, Robert A. Goodnow, José S. Duca, Johanna M. Jansen, Thomas S. Rush and Jennifer Listgarten. Their work appears in journals such as Journal of Computer-Aided Molecular Design, Bioorganic & Medicinal Chemistry Letters, Molecular Cancer Therapeutics, Nature Reviews Drug Discovery and Journal of Medicinal Chemistry.
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.