Teh‐Yung Liu
- Molecular Biology top 10%
- Immunology top 10%
- Epidemiology
- Public Health, Environmental and Occupational Health top 10%
- Organic Chemistry top 10%
- Co-authors
- E C GotschlichS. D. ElliottA.S. InglisJohn B. RobbinsWilliam H. SteinStanford MooreAlexander A. KorttKlaus Hofmann
- Topics
- Biochemical and Structural Characterization (10 papers)Peptidase Inhibition and Analysis (9 papers)Glycosylation and Glycoproteins Research (8 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyJournal of Biological Chemistry
- Partner nations
- United StatesTaiwanCameroon
In The Last Decade
Teh‐Yung Liu
47 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 111
- Molecular Biology 886
- Immunology 259
- Epidemiology 230
- Public Health, Environmental and Occupational Health 225
- Organic Chemistry 206
Countries citing papers authored by Teh‐Yung Liu
This map shows the geographic impact of Teh‐Yung Liu'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 Teh‐Yung Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teh‐Yung Liu more than expected).
Fields of papers citing papers by Teh‐Yung Liu
This network shows the impact of papers produced by Teh‐Yung Liu. 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 Teh‐Yung Liu. The network helps show where Teh‐Yung Liu may publish in the future.
Co-authorship network of co-authors of Teh‐Yung Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Teh‐Yung Liu. A scholar is included among the top collaborators of Teh‐Yung Liu 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 Teh‐Yung Liu. Teh‐Yung Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 104 | |
| 3 | 43 | |
| 4 | 34 | |
| 5 | 1 | |
| 6 | 13 | |
| 7 | 16 | |
| 8 | 6 | |
| 9 | 3 | |
| 10 | 19 | |
| 11 | 19 | |
| 12 | 9 | |
| 13 | Biochemical and biophysical studies of proteins and nucleic acids | 25 |
| 14 | 13 | |
| 15 | 42 | |
| 16 | 33 | |
| 17 | 18 | |
| 18 | 73 | |
| 19 | 8 | |
| 20 | 47 |
About Teh‐Yung Liu
Teh‐Yung Liu is a scholar working on Biochemistry, Molecular Biology and Endocrinology, having authored 48 papers that have together received 1.7k indexed citations. Recurring topics across this work include Biochemical and Structural Characterization (10 papers), Peptidase Inhibition and Analysis (9 papers) and Glycosylation and Glycoproteins Research (8 papers). The work is most often cited by research in Microbiology (121 citations), Endocrinology (84 citations) and Molecular Biology (886 citations). Teh‐Yung Liu has collaborated with scholars based in United States, Taiwan and Cameroon. Frequent co-authors include E C Gotschlich, S. D. Elliott, A.S. Inglis, John B. Robbins, William H. Stein, Stanford Moore, Alexander A. Kortt, Klaus Hofmann, Haruaki Yajima and Noboru Yanaihara. 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.