Daniel J. Frank
Impact in
- Pharmacology top 2%
- Pharmacogenetics and Drug Metabolism
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- Hedgehog Signaling Pathway Studies
- Epigenetics and DNA Methylation
- Steroid Chemistry and Biochemistry
Papers in
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- Steroid Chemistry and Biochemistry 4
- Hedgehog Signaling Pathway Studies 2
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- Pharmacogenetics and Drug Metabolism 9
- Co-authors
- Stephen G. Sligar (4 shared papers)Ilia G. Denisov (3 shared papers)David Walterhouse (2 shared papers)Philip M. Iannaccone (2 shared papers)Joon Won Yoon (2 shared papers)Yasuhiro Kita (1 shared paper)Rebecca R. Majewski (1 shared paper)Howard J. Jacob (1 shared paper)
- Journals
- Journal of Biological Chemistry (4 papers)Biochemistry (3 papers)ASAIO Journal (3 papers)Frontiers in Immunology (1 paper)The Annals of Thoracic Surgery (1 paper)
- Partner nations
- United StatesAustraliaSpain
In The Last Decade
Daniel J. Frank
17 papers receiving 746 citations
Peers
Comparison fields: 5 of 89
- Pharmacology 247
- Molecular Biology 461
- Oncology 131
- Computational Theory and Mathematics 66
- Infectious Diseases 69
Countries citing papers authored by Daniel J. Frank
This map shows the geographic impact of Daniel J. Frank'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 J. Frank with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Frank more than expected).
Fields of papers citing papers by Daniel J. Frank
This network shows the impact of papers produced by Daniel J. Frank. 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 J. Frank. The network helps show where Daniel J. Frank may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel J. Frank, 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 | 2002 | 265 | |
| 2 | 2009 | 94 | |
| 3 | 2001 | 72 | |
| 4 | 2009 | 47 | |
| 5 | 2013 | 45 | |
| 6 | 2002 | 34 | |
| 7 | 2018 | 30 | |
| 8 | 2014 | 29 | |
| 9 | 2010 | 28 | |
| 10 | 2009 | 22 | |
| 11 | 2014 | 20 | |
| 12 | 2015 | 19 | |
| 13 | 2015 | 18 | |
| 14 | 2021 | 17 | |
| 15 | 2016 | 16 | |
| 16 | 2004 | 1 | |
| 17 | 2004 | 1 | |
| 18 | 2000 | 0 |
About Daniel J. Frank
Daniel J. Frank is a scholar working on Molecular Biology, Pharmacology, Surgery, Biomedical Engineering and Inorganic Chemistry, having authored 18 papers that have together received 758 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (9 papers), Steroid Chemistry and Biochemistry (4 papers), Mechanical Circulatory Support Devices (4 papers), Cardiac Structural Anomalies and Repair (3 papers), Metal-Catalyzed Oxygenation Mechanisms (3 papers), Molecular spectroscopy and chirality (2 papers), Analytical Chemistry and Chromatography (2 papers) and Hedgehog Signaling Pathway Studies (2 papers). The work is most often cited by research in Pharmacology (247 citations), Molecular Biology (461 citations), Oncology (131 citations), Computational Theory and Mathematics (66 citations) and Infectious Diseases (69 citations). Daniel J. Frank has collaborated with scholars based in United States, Australia and Spain. Frequent co-authors include Stephen G. Sligar, Ilia G. Denisov, David Walterhouse, Philip M. Iannaccone, Joon Won Yoon, Yasuhiro Kita, Rebecca R. Majewski, Howard J. Jacob, Marcelo A. Nóbrega and Paul R. Ortiz de Montellano. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry, ASAIO Journal, Frontiers in Immunology and The Annals of Thoracic Surgery.
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.