Hua-Poo Su
Impact in
- Virology top 2%
- Poxvirus research and outbreaks
- Microbiology top 5%
- Reproductive tract infections research
Papers in
- Virology 7
- Poxvirus research and outbreaks 6
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- HIV/AIDS drug development and treatment 5
- Co-authors
- David N. Garboczi (10 shared papers)Apostolos G. Gittis (5 shared papers)Kavita Singh (5 shared papers)David Yin-wei Lin (2 shared papers)Kodi S. Ravichandran (3 shared papers)Yoshimasa Tanaka (1 shared paper)Masashi Iwasaki (1 shared paper)Bunzo Mikami (1 shared paper)
- Journals
- Journal of Virology (7 papers)Bioorganic & Medicinal Chemistry Letters (6 papers)Proceedings of the National Academy of Sciences (3 papers)Journal of Biological Chemistry (3 papers)ACS Medicinal Chemistry Letters (2 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Hua-Poo Su
37 papers receiving 2k citations
Peers
Comparison fields: 5 of 80
- Virology 366
- Microbiology 110
- Immunology 336
- Oncology 324
- Computational Theory and Mathematics 142
Countries citing papers authored by Hua-Poo Su
This map shows the geographic impact of Hua-Poo Su'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 Hua-Poo Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hua-Poo Su more than expected).
Fields of papers citing papers by Hua-Poo Su
This network shows the impact of papers produced by Hua-Poo Su. 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 Hua-Poo Su. The network helps show where Hua-Poo Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Hua-Poo Su, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 389 | |
| 2 | 2002 | 211 | |
| 3 | 2008 | 153 | |
| 4 | 2019 | 124 | |
| 5 | 2008 | 101 | |
| 6 | 2010 | 87 | |
| 7 | 1995 | 77 | |
| 8 | 2005 | 71 | |
| 9 | 2011 | 67 | |
| 10 | 2007 | 63 | |
| 11 | 2005 | 61 | |
| 12 | 2014 | 54 | |
| 13 | 2000 | 52 | |
| 14 | 2016 | 46 | |
| 15 | 2000 | 45 | |
| 16 | 2000 | 45 | |
| 17 | 2016 | 45 | |
| 18 | 2008 | 44 | |
| 19 | 2009 | 43 | |
| 20 | 2017 | 39 |
About Hua-Poo Su
Hua-Poo Su is a scholar working on Virology, Infectious Diseases, Immunology, Microbiology and Physiology, having authored 37 papers that have together received 2.1k indexed citations. Recurring topics across this work include Poxvirus research and outbreaks (6 papers), HIV/AIDS drug development and treatment (5 papers), Respiratory viral infections research (3 papers), Enzyme Structure and Function (3 papers), Computational Drug Discovery Methods (3 papers), Alzheimer's disease research and treatments (2 papers), Malaria Research and Control (2 papers) and T-cell and B-cell Immunology (2 papers). The work is most often cited by research in Virology (366 citations), Microbiology (110 citations), Immunology (336 citations), Oncology (324 citations) and Computational Theory and Mathematics (142 citations). Hua-Poo Su has collaborated with scholars based in United States, China and Japan. Frequent co-authors include David N. Garboczi, Apostolos G. Gittis, Kavita Singh, David Yin-wei Lin, Kodi S. Ravichandran, Yoshimasa Tanaka, Masashi Iwasaki, Bunzo Mikami, Tasuku Honjo and Taku Okazaki. Their work appears in journals such as Journal of Virology, Bioorganic & Medicinal Chemistry Letters, Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and ACS Medicinal Chemistry Letters.
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.