Thomas K. H. Chang
- Pharmacology top 0.01%
- Molecular Biology top 2%
- Oncology top 0.5%
- Endocrinology, Diabetes and Metabolism top 0.5%
- Biochemistry top 0.1%
- Co-authors
- Wayne LevinDene E. RyanDavid J. WaxmanLinda M. ReikCharles L. CrespiFrank S. AbbottAlexander W. WoodGeorg F. Weber
- Topics
- Pharmacogenetics and Drug Metabolism (117 papers)Drug Transport and Resistance Mechanisms (37 papers)Eicosanoids and Hypertension Pharmacology (21 papers)
- Cited by
- PharmacologyBiochemistryOncology
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyJournal of Biological Chemistry
- Partner nations
- United StatesCanadaIndia
In The Last Decade
Thomas K. H. Chang
222 papers receiving 11.5k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Pharmacology 6.4k
- Molecular Biology 3.9k
- Oncology 3.0k
- Endocrinology, Diabetes and Metabolism 1.3k
- Biochemistry 1.3k
Countries citing papers authored by Thomas K. H. Chang
This map shows the geographic impact of Thomas K. H. Chang'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 Thomas K. H. Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas K. H. Chang more than expected).
Fields of papers citing papers by Thomas K. H. Chang
This network shows the impact of papers produced by Thomas K. H. Chang. 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 Thomas K. H. Chang. The network helps show where Thomas K. H. Chang may publish in the future.
Co-authorship network of co-authors of Thomas K. H. Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Thomas K. H. Chang. A scholar is included among the top collaborators of Thomas K. H. Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Thomas K. H. Chang. Thomas K. H. Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 111 | |
| 2 | 6 | |
| 3 | 16 | |
| 4 | 17 | |
| 5 | 8 | |
| 6 | 123 | |
| 7 | 28 | |
| 8 | 31 | |
| 9 | 53 | |
| 10 | 17 | |
| 11 | 23 | |
| 12 | 40 | |
| 13 | 2 | |
| 14 | 56 | |
| 15 | 48 | |
| 16 | 80 | |
| 17 | 85 | |
| 18 | 31 | |
| 19 | 12 | |
| 20 | Regulation of rat liver cytochrome P450j, a high affinity N-nitrosodimethylamine demethylase (NDMAD) | 2 |
About Thomas K. H. Chang
Thomas K. H. Chang is a scholar working on Pharmacology, Biochemistry and Endocrinology, Diabetes and Metabolism, having authored 222 papers that have together received 12.1k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (117 papers), Drug Transport and Resistance Mechanisms (37 papers) and Eicosanoids and Hypertension Pharmacology (21 papers). The work is most often cited by research in Pharmacology (6.4k citations), Biochemistry (1.3k citations) and Oncology (3.0k citations). Thomas K. H. Chang has collaborated with scholars based in United States, Canada and India. Frequent co-authors include Wayne Levin, Dene E. Ryan, David J. Waxman, Linda M. Reik, Charles L. Crespi, Frank S. Abbott, Alexander W. Wood, Georg F. Weber, Frank J. Gonzalez and Vincent Tong. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological 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.