Jay T. Goodwin
Impact in
-
- Computational Drug Discovery Methods
- Pharmaceutical Science top 10%
Papers in
-
- RNA and protein synthesis mechanisms 8
- Protein Structure and Dynamics 5
- DNA and Nucleic Acid Chemistry 5
- Advanced biosensing and bioanalysis techniques 4
- Chemical Synthesis and Analysis 3
- Co-authors
- David G. Lynn (6 shared papers)Philip S. Burton (8 shared papers)Gary D. Glick (6 shared papers)David E. Clark (1 shared paper)Robert A. Conradi (5 shared papers)Thomas J. Vidmar (2 shared papers)Benny Amore (2 shared papers)Anil Mehta (3 shared papers)
- Journals
- Journal of the American Chemical Society (4 papers)Journal of Medicinal Chemistry (3 papers)Tetrahedron Letters (3 papers)The Journal of Organic Chemistry (3 papers)Journal of Pharmacology and Experimental Therapeutics (2 papers)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Jay T. Goodwin
27 papers receiving 918 citations
Peers
Comparison fields: 5 of 104
- Computational Theory and Mathematics 158
- Pharmaceutical Science 47
- Molecular Biology 508
- Organic Chemistry 213
- Spectroscopy 113
Countries citing papers authored by Jay T. Goodwin
This map shows the geographic impact of Jay T. Goodwin'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 Jay T. Goodwin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay T. Goodwin more than expected).
Fields of papers citing papers by Jay T. Goodwin
This network shows the impact of papers produced by Jay T. Goodwin. 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 Jay T. Goodwin. The network helps show where Jay T. Goodwin may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay T. Goodwin, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 130 | |
| 2 | 1992 | 119 | |
| 3 | 2005 | 84 | |
| 4 | 2001 | 77 | |
| 5 | 1989 | 77 | |
| 6 | 2002 | 67 | |
| 7 | 2017 | 64 | |
| 8 | 1996 | 45 | |
| 9 | 2012 | 45 | |
| 10 | 1993 | 33 | |
| 11 | 1999 | 28 | |
| 12 | 1997 | 23 | |
| 13 | 1994 | 22 | |
| 14 | 2019 | 22 | |
| 15 | 2017 | 15 | |
| 16 | 1999 | 15 | |
| 17 | 1960 | 14 | |
| 18 | 2000 | 13 | |
| 19 | 2021 | 11 | |
| 20 | 2015 | 11 |
About Jay T. Goodwin
Jay T. Goodwin is a scholar working on Molecular Biology, Organic Chemistry, Astronomy and Astrophysics, Oncology and Computational Theory and Mathematics, having authored 27 papers that have together received 959 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (8 papers), Protein Structure and Dynamics (5 papers), DNA and Nucleic Acid Chemistry (5 papers), Drug Transport and Resistance Mechanisms (4 papers), Computational Drug Discovery Methods (4 papers), Origins and Evolution of Life (4 papers), Advanced biosensing and bioanalysis techniques (4 papers) and Chemical Synthesis and Analysis (3 papers). The work is most often cited by research in Computational Theory and Mathematics (158 citations), Pharmaceutical Science (47 citations), Molecular Biology (508 citations), Organic Chemistry (213 citations) and Spectroscopy (113 citations). Jay T. Goodwin has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include David G. Lynn, Philip S. Burton, Gary D. Glick, David E. Clark, Robert A. Conradi, Thomas J. Vidmar, Benny Amore, Anil Mehta, Norman F.H. Ho and Richard Cole. Their work appears in journals such as Journal of the American Chemical Society, Journal of Medicinal Chemistry, Tetrahedron Letters, The Journal of Organic Chemistry and Journal of Pharmacology and Experimental Therapeutics.
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.