Ta C. Wu
Impact in
- Pharmacology top 1%
- Pharmacogenetics and Drug Metabolism
- Antibiotics Pharmacokinetics and Efficacy
- Pharmaceutical Science top 2%
- Drug Solubulity and Delivery Systems
Papers in
-
- Pharmacological Effects and Toxicity Studies 3
- Pharmaceutical studies and practices 1
- Oncology 4
- Drug Transport and Resistance Mechanisms 4
- Co-authors
- Win L. Chiou (7 shared papers)Sang M. Chung (6 shared papers)B Booth (1 shared paper)Eva Gil Berglund (1 shared paper)K S Reynolds (1 shared paper)Rajanikanth Madabushi (1 shared paper)Ping Zhao (1 shared paper)Joseph A. Grillo (1 shared paper)
- Journals
- Pharmaceutical Research (4 papers)Clinical Pharmacology & Therapeutics (2 papers)International Journal of Clinical Pharmacology and Therapeutics (2 papers)
- Partner nations
- United StatesBelgiumSweden
In The Last Decade
Ta C. Wu
8 papers receiving 774 citations
Ta C. Wu's Hit Papers
Peers
Comparison fields: 5 of 92
- Pharmacology 273
- Pharmaceutical Science 146
- Oncology 279
- Pediatrics, Perinatology and Child Health 160
- Transplantation 21
Countries citing papers authored by Ta C. Wu
This map shows the geographic impact of Ta C. Wu'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 Ta C. Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ta C. Wu more than expected).
Fields of papers citing papers by Ta C. Wu
This network shows the impact of papers produced by Ta C. Wu. 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 Ta C. Wu. The network helps show where Ta C. Wu may publish in the future.
Co-authors
The 18 scholars most cited alongside Ta C. Wu, 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 | Applications of Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation During Regulatory Review Hit paper breakdown → | 2010 | 408 |
| 2 | 2000 | 125 | |
| 3 | 2001 | 80 | |
| 4 | 2001 | 73 | |
| 5 | 2000 | 33 | |
| 6 | 2000 | 33 | |
| 7 | 2000 | 30 | |
| 8 | 2001 | 14 |
About Ta C. Wu
Ta C. Wu is a scholar working on Pediatrics, Perinatology and Child Health, Oncology, Pharmacology, Genetics and Statistics and Probability, having authored 8 papers that have together received 796 indexed citations. Recurring topics across this work include Drug Transport and Resistance Mechanisms (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Pharmacological Effects and Toxicity Studies (3 papers), Hemoglobinopathies and Related Disorders (1 paper), Statistical Methods in Clinical Trials (1 paper) and Pharmaceutical studies and practices (1 paper). The work is most often cited by research in Pharmacology (273 citations), Pharmaceutical Science (146 citations), Oncology (279 citations), Pediatrics, Perinatology and Child Health (160 citations) and Transplantation (21 citations). Ta C. Wu has collaborated with scholars based in United States, Belgium and Sweden. Frequent co-authors include Win L. Chiou, Sang M. Chung, B Booth, Eva Gil Berglund, K S Reynolds, Rajanikanth Madabushi, Ping Zhao, Joseph A. Grillo, Young‐Jin Moon and Nam Atiqur Rahman. Their work appears in journals such as Pharmaceutical Research, Clinical Pharmacology & Therapeutics and International Journal of Clinical Pharmacology and 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.