Shih-Chieh Su
Impact in
- Structural Biology top 10%
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
Papers in
-
- Machine Learning in Bioinformatics 7
- Protein Structure and Dynamics 7
- RNA and protein synthesis mechanisms 6
- Signaling Pathways in Disease 2
-
- SARS-CoV-2 and COVID-19 Research 5
- Viral gastroenteritis research and epidemiology 3
- Co-authors
- Kang-Hao Liang (5 shared papers)Han‐Chung Wu (6 shared papers)Feng-Yi Ke (3 shared papers)Shih-Han Ko (4 shared papers)Ruei‐Min Lu (2 shared papers)Cheng‐Jian Lin (3 shared papers)Chung‐I Chang (5 shared papers)Kou‐Juey Wu (1 shared paper)
- Journals
- Journal of Biomedical Science (4 papers)Structure (2 papers)Autophagy (1 paper)IEEE Signal Processing Magazine (1 paper)The International Journal of Biochemistry & Cell Biology (1 paper)
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Shih-Chieh Su
28 papers receiving 586 citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Structural Biology 17
- Infectious Diseases 197
- Molecular Biology 316
- Cancer Research 41
- Computational Theory and Mathematics 39
Countries citing papers authored by Shih-Chieh Su
This map shows the geographic impact of Shih-Chieh 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 Shih-Chieh Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih-Chieh Su more than expected).
Fields of papers citing papers by Shih-Chieh Su
This network shows the impact of papers produced by Shih-Chieh 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 Shih-Chieh Su. The network helps show where Shih-Chieh Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Shih-Chieh 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Monoclonal antibodies for COVID-19 therapy and SARS-CoV-2 detection Hit paper breakdown → | 2022 | 157 |
| 2 | 2022 | 94 | |
| 3 | 2015 | 76 | |
| 4 | 2016 | 28 | |
| 5 | 2016 | 28 | |
| 6 | 2011 | 25 | |
| 7 | 2011 | 24 | |
| 8 | 2015 | 23 | |
| 9 | 1987 | 18 | |
| 10 | 2015 | 16 | |
| 11 | 2021 | 15 | |
| 12 | 2021 | 14 | |
| 13 | 2013 | 12 | |
| 14 | 2004 | 11 | |
| 15 | 2007 | 11 | |
| 16 | 2015 | 10 | |
| 17 | 2022 | 7 | |
| 18 | 2023 | 5 | |
| 19 | 2016 | 5 | |
| 20 | 2011 | 4 |
About Shih-Chieh Su
Shih-Chieh Su is a scholar working on Molecular Biology, Infectious Diseases, Materials Chemistry, Epidemiology and Artificial Intelligence, having authored 28 papers that have together received 599 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (7 papers), Protein Structure and Dynamics (7 papers), RNA and protein synthesis mechanisms (6 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Enzyme Structure and Function (4 papers), Viral gastroenteritis research and epidemiology (3 papers), Signaling Pathways in Disease (2 papers) and Animal Virus Infections Studies (2 papers). The work is most often cited by research in Structural Biology (17 citations), Infectious Diseases (197 citations), Molecular Biology (316 citations), Cancer Research (41 citations) and Computational Theory and Mathematics (39 citations). Shih-Chieh Su has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Kang-Hao Liang, Han‐Chung Wu, Feng-Yi Ke, Shih-Han Ko, Ruei‐Min Lu, Cheng‐Jian Lin, Chung‐I Chang, Kou‐Juey Wu, Jyh-Jong Tsay and Chia‐Yang Li. Their work appears in journals such as Journal of Biomedical Science, Structure, Autophagy, IEEE Signal Processing Magazine and The International Journal of Biochemistry & Cell Biology.
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.