Kai‐Tai Chang
- Molecular Medicine top 1%
- Pharmacology top 5%
- Epidemiology
- Applied Microbiology and Biotechnology top 1%
- Molecular Biology
- Co-authors
- Vincent H. TamKimberly R. LedesmaKamilia AbdelraoufKevin W. GareyHenrietta AbodakpiSong GaoMichael NikolaouAna María Sánchez‐Díaz
- Topics
- Antibiotic Resistance in Bacteria (19 papers)Antibiotics Pharmacokinetics and Efficacy (18 papers)Antibiotic Use and Resistance (6 papers)
- Journals
- Antimicrobial Agents and ChemotherapyJournal of Antimicrobial ChemotherapyClinical Microbiology and Infection
- Partner nations
- United StatesSpainCanada
In The Last Decade
Kai‐Tai Chang
20 papers receiving 539 citations
Peers
Comparison fields: 5 of 69
- Molecular Medicine 402
- Pharmacology 320
- Epidemiology 155
- Applied Microbiology and Biotechnology 147
- Molecular Biology 116
Countries citing papers authored by Kai‐Tai Chang
This map shows the geographic impact of Kai‐Tai 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 Kai‐Tai Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai‐Tai Chang more than expected).
Fields of papers citing papers by Kai‐Tai Chang
This network shows the impact of papers produced by Kai‐Tai 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 Kai‐Tai Chang. The network helps show where Kai‐Tai Chang may publish in the future.
Co-authorship network of co-authors of Kai‐Tai Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Kai‐Tai Chang. A scholar is included among the top collaborators of Kai‐Tai 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 Kai‐Tai Chang. Kai‐Tai 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 | 14 | |
| 2 | 27 | |
| 3 | 76 | |
| 4 | 27 | |
| 5 | 10 | |
| 6 | 20 | |
| 7 | 47 | |
| 8 | 10 | |
| 9 | 5 | |
| 10 | 8 | |
| 11 | 26 | |
| 12 | 21 | |
| 13 | 13 | |
| 14 | 121 | |
| 15 | 16 | |
| 16 | 15 | |
| 17 | 15 | |
| 18 | 31 | |
| 19 | 19 | |
| 20 | 39 |
About Kai‐Tai Chang
Kai‐Tai Chang is a scholar working on Molecular Medicine, Applied Microbiology and Biotechnology and Pharmacology, having authored 20 papers that have together received 560 indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (19 papers), Antibiotics Pharmacokinetics and Efficacy (18 papers) and Antibiotic Use and Resistance (6 papers). The work is most often cited by research in Molecular Medicine (402 citations), Applied Microbiology and Biotechnology (147 citations) and Pharmacology (320 citations). Kai‐Tai Chang has collaborated with scholars based in United States, Spain and Canada. Frequent co-authors include Vincent H. Tam, Kimberly R. Ledesma, Kamilia Abdelraouf, Kevin W. Garey, Henrietta Abodakpi, Song Gao, Michael Nikolaou, Ana María Sánchez‐Díaz, Magdalene Ameka and Rafael Cantón. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, Journal of Antimicrobial Chemotherapy and Clinical Microbiology and Infection.
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.