Yu‐Tsueng Liu
- Molecular Biology top 5%
- Immunology top 5%
- Epidemiology top 10%
- Computational Theory and Mathematics top 2%
- Infectious Diseases top 5%
- Co-authors
- Trey IdekerEunjung LeeDoheon LeeHan‐Yu ChuangCarol ShenEyal RazJong‐Dae LeeKyoko Katakura
- Topics
- Genomic variations and chromosomal abnormalities (4 papers)Cancer Genomics and Diagnostics (4 papers)Hepatitis C virus research (4 papers)
- Partner nations
- United StatesTaiwanMozambique
In The Last Decade
Yu‐Tsueng Liu
28 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Molecular Biology 1.4k
- Immunology 488
- Epidemiology 309
- Computational Theory and Mathematics 278
- Infectious Diseases 268
Countries citing papers authored by Yu‐Tsueng Liu
This map shows the geographic impact of Yu‐Tsueng 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 Yu‐Tsueng Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Tsueng Liu more than expected).
Fields of papers citing papers by Yu‐Tsueng Liu
This network shows the impact of papers produced by Yu‐Tsueng 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 Yu‐Tsueng Liu. The network helps show where Yu‐Tsueng Liu may publish in the future.
Co-authorship network of co-authors of Yu‐Tsueng Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Tsueng Liu. A scholar is included among the top collaborators of Yu‐Tsueng 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 Yu‐Tsueng Liu. Yu‐Tsueng 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 | 2 | |
| 2 | 0 | |
| 3 | 9 | |
| 4 | 7 | |
| 5 | HPV16/18 and p16 gene expression in ocular surface squamous neoplasia: a retrospective cross-sectional analysis | 1 |
| 6 | 14 | |
| 7 | Vaccination with Killed but Metabolically Active E. coli Over-expressing Hemagglutinin Elicits Neutralizing Antibodies to H1N1 Swine Origin Influenza A Virus. | 1 |
| 8 | 7 | |
| 9 | 17 | |
| 10 | 55 | |
| 11 | 18 | |
| 12 | 38 | |
| 13 | 21 | |
| 14 | 8 | |
| 15 | 12 | |
| 16 | 3 | |
| 17 | 18 | |
| 18 | 493 | |
| 19 | 326 | |
| 20 | 22 |
About Yu‐Tsueng Liu
Yu‐Tsueng Liu is a scholar working on Hepatology, Cancer Research and Immunology, having authored 29 papers that have together received 2.4k indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (4 papers), Cancer Genomics and Diagnostics (4 papers) and Hepatitis C virus research (4 papers). The work is most often cited by research in Immunology (488 citations), Molecular Biology (1.4k citations) and Computational Theory and Mathematics (278 citations). Yu‐Tsueng Liu has collaborated with scholars based in United States, Taiwan and Mozambique. Frequent co-authors include Trey Ideker, Eunjung Lee, Doheon Lee, Han‐Yu Chuang, Carol Shen, Eyal Raz, Jong‐Dae Lee, Kyoko Katakura, Gady Cojocaru and Steve Shenouda. Their work appears in journals such as Proceedings of the National Academy of Sciences, Blood and Bioinformatics.
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.