Yi Hsiao
Impact in
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- Computational Drug Discovery Methods
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- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
Papers in
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- vaccines and immunoinformatics approaches 2
- Glycosylation and Glycoproteins Research 1
- Identification and Quantification in Food 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Yufeng Jane Tseng (2 shared papers)Bo‐Han Su (1 shared paper)Hsueh‐Fen Juan (1 shared paper)Chien‐Yu Chen (1 shared paper)Yu‐Chuan Chang (1 shared paper)Hsuan‐Cheng Huang (1 shared paper)Hsin‐Hsiang Chung (1 shared paper)Ting-Hao Kuo (1 shared paper)
- Journals
- Nucleic Acids Research (1 paper)Nature Communications (1 paper)Briefings in Bioinformatics (1 paper)Clinical and Experimental Dermatology (1 paper)ACS Applied Polymer Materials (1 paper)
- Partner nations
- TaiwanUnited StatesUnited Kingdom
In The Last Decade
Yi Hsiao
7 papers receiving 116 citations
Peers
Comparison fields: 5 of 53
- Computational Theory and Mathematics 45
- Infectious Diseases 24
- Spectroscopy 15
- Molecular Biology 57
- Pharmacology 7
Countries citing papers authored by Yi Hsiao
This map shows the geographic impact of Yi Hsiao'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 Yi Hsiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Hsiao more than expected).
Fields of papers citing papers by Yi Hsiao
This network shows the impact of papers produced by Yi Hsiao. 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 Yi Hsiao. The network helps show where Yi Hsiao may publish in the future.
Co-authors
The 24 scholars most cited alongside Yi Hsiao, 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 | 2020 | 42 | |
| 2 | 2020 | 27 | |
| 3 | 2019 | 17 | |
| 4 | 2023 | 11 | |
| 5 | 1992 | 9 | |
| 6 | 2020 | 6 | |
| 7 | 2013 | 4 |
About Yi Hsiao
Yi Hsiao is a scholar working on Molecular Biology, Computational Theory and Mathematics, Infectious Diseases, Dermatology and Atomic and Molecular Physics, and Optics, having authored 7 papers that have together received 116 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), vaccines and immunoinformatics approaches (2 papers), Pharmacogenetics and Drug Metabolism (1 paper), Genetic and rare skin diseases. (1 paper), Glycosylation and Glycoproteins Research (1 paper), Identification and Quantification in Food (1 paper), Peptidase Inhibition and Analysis (1 paper) and Advanced Chemical Physics Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (45 citations), Infectious Diseases (24 citations), Spectroscopy (15 citations), Molecular Biology (57 citations) and Pharmacology (7 citations). Yi Hsiao has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Yufeng Jane Tseng, Bo‐Han Su, Hsueh‐Fen Juan, Chien‐Yu Chen, Yu‐Chuan Chang, Hsuan‐Cheng Huang, Hsin‐Hsiang Chung, Ting-Hao Kuo, Cheng‐Chih Hsu and Jed W. Pitera. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Briefings in Bioinformatics, Clinical and Experimental Dermatology and ACS Applied Polymer Materials.
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.