Daniel S. Sem
- Biochemistry top 5%
- Pharmacology top 2%
- Pharmacogenetics and Drug Metabolism 10
- Spectroscopy top 5%
- Molecular Biology top 10%
- Protein Structure and Dynamics 13
- ATP Synthase and ATPases Research 8
- Protein Tyrosine Phosphatases 8
- Metabolomics and Mass Spectrometry Studies 6
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- Computational Drug Discovery Methods 16
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- Estrogen and related hormone effects 15
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- Enzyme Structure and Function 10
- Co-authors
- Maurizio PellecchiaKurt WüthrichCharles B. KasperPhani Kumar PullelaTaurai ChikuMichael J. CarvanJohn E. ThomasR M Jack
- Cited by
- BiochemistryPharmacologySpectroscopy
- Journals
- Biochemistry (12 papers)Proteins Structure Function and Bioinformatics (4 papers)The FASEB Journal (4 papers)
- Partner nations
- United StatesThailandZimbabwe
In The Last Decade
Daniel S. Sem
86 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Biochemistry 162
- Pharmacology 186
- Spectroscopy 286
- Molecular Biology 1.1k
- Computational Theory and Mathematics 238
Countries citing papers authored by Daniel S. Sem
This map shows the geographic impact of Daniel S. Sem'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 S. Sem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Sem more than expected).
Fields of papers citing papers by Daniel S. Sem
This network shows the impact of papers produced by Daniel S. Sem. 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 S. Sem. The network helps show where Daniel S. Sem may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel S. Sem, 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 | 2025 | 1 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 1 | |
| 5 | 2015 | 11 | |
| 6 | Repurposing - Finding New Uses for Old (and Patented) Drugs: Bridging the "Valley of Death," to Translate Academic Research Into New Medicines | 2014 | 1 |
| 7 | 2014 | 13 | |
| 8 | 2013 | 8 | |
| 9 | 2012 | 7 | |
| 10 | 2009 | 7 | |
| 11 | 2009 | 61 | |
| 12 | 2007 | 36 | |
| 13 | 2007 | 27 | |
| 14 | 2006 | 4 | |
| 15 | 2004 | 13 | |
| 16 | 2004 | 4 | |
| 17 | 2003 | 12 | |
| 18 | 2001 | 13 | |
| 19 | 1999 | 17 | |
| 20 | 1997 | 26 |
About Daniel S. Sem
Daniel S. Sem is a scholar working on Pharmacology, Computational Theory and Mathematics and Toxicology, having authored 86 papers that have together received 1.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), Estrogen and related hormone effects (15 papers), Protein Structure and Dynamics (13 papers), Pharmacogenetics and Drug Metabolism (10 papers), Enzyme Structure and Function (10 papers), ATP Synthase and ATPases Research (8 papers), Protein Tyrosine Phosphatases (8 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). The work is most often cited by research in Biochemistry (162 citations), Pharmacology (186 citations) and Spectroscopy (286 citations). Daniel S. Sem has collaborated with scholars based in United States, Thailand and Zimbabwe. Frequent co-authors include Maurizio Pellecchia, Kurt Wüthrich, Charles B. Kasper, Phani Kumar Pullela, Taurai Chiku, Michael J. Carvan, John E. Thomas, R M Jack, Anna L. Shen and David Meininger. Their work appears in journals such as Biochemistry, Proteins Structure Function and Bioinformatics, The FASEB Journal, Journal of Medicinal Chemistry and BMC Biochemistry.
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.