David T. Stanton
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Spectroscopy top 2%
- Analytical Chemistry and Chromatography
Papers in
-
- Computational Drug Discovery Methods 19
- Spectroscopy 13
- Analytical Chemistry and Chromatography 11
- Co-authors
- Peter C. JursManuel ZarzoMartin G. HicksDebra A. TireyKenneth L. MorandJ. David PinkstonRajarshi GuhaSandra L. Nelson
- Journals
- Environmental Toxicology and Chemistry (4 papers)SLAS DISCOVERY (3 papers)Analytical Chemistry (3 papers)Journal of Computer-Aided Molecular Design (2 papers)Journal of Agricultural and Food Chemistry (2 papers)
- Partner nations
- United StatesAustraliaNorway
In The Last Decade
David T. Stanton
38 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Computational Theory and Mathematics 829
- Spectroscopy 522
- Analytical Chemistry 204
- Sensory Systems 92
- Organic Chemistry 472
Countries citing papers authored by David T. Stanton
This map shows the geographic impact of David T. Stanton'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 David T. Stanton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Stanton more than expected).
Fields of papers citing papers by David T. Stanton
This network shows the impact of papers produced by David T. Stanton. 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 David T. Stanton. The network helps show where David T. Stanton may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David T. Stanton, 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 | 2021 | 12 | |
| 2 | 2014 | 22 | |
| 3 | 2012 | 53 | |
| 4 | 2011 | 18 | |
| 5 | 2009 | 70 | |
| 6 | 2008 | 10 | |
| 7 | 2007 | 6 | |
| 8 | 2006 | 30 | |
| 9 | 2004 | 46 | |
| 10 | 2003 | 55 | |
| 11 | 2003 | 77 | |
| 12 | 2003 | 10 | |
| 13 | 2002 | 6 | |
| 14 | 2001 | 43 | |
| 15 | 2000 | 41 | |
| 16 | 1999 | 16 | |
| 17 | 1998 | 72 | |
| 18 | 1993 | 10 | |
| 19 | 1991 | 35 | |
| 20 | 1989 | 60 |
About David T. Stanton
David T. Stanton is a scholar working on Computational Theory and Mathematics, Spectroscopy, Analytical Chemistry, Filtration and Separation and Sensory Systems, having authored 39 papers that have together received 1.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (19 papers), Analytical Chemistry and Chromatography (11 papers), Free Radicals and Antioxidants (6 papers), Analytical Methods in Pharmaceuticals (4 papers), Synthesis and biological activity (3 papers), Cancer therapeutics and mechanisms (3 papers), Protein Structure and Dynamics (2 papers) and Advanced Chemical Sensor Technologies (2 papers). The work is most often cited by research in Computational Theory and Mathematics (829 citations), Spectroscopy (522 citations), Analytical Chemistry (204 citations), Sensory Systems (92 citations) and Organic Chemistry (472 citations). David T. Stanton has collaborated with scholars based in United States, Australia and Norway. Frequent co-authors include Peter C. Jurs, Manuel Zarzo, Martin G. Hicks, Debra A. Tirey, Kenneth L. Morand, J. David Pinkston, Rajarshi Guha, Sandra L. Nelson, Lisa E. Williams and José Melena. Their work appears in journals such as Environmental Toxicology and Chemistry, SLAS DISCOVERY, Analytical Chemistry, Journal of Computer-Aided Molecular Design and Journal of Agricultural and Food 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.