Shih-Han Ko
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Viral gastroenteritis research and epidemiology
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- Animal Virus Infections Studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 5
- SARS-CoV-2 detection and testing 3
- COVID-19 Clinical Research Studies 3
- Viral gastroenteritis research and epidemiology 2
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- RNA Interference and Gene Delivery 2
- Co-authors
- Han‐Chung Wu (8 shared papers)Ruei‐Min Lu (6 shared papers)Kang-Hao Liang (5 shared papers)Shih-Chieh Su (4 shared papers)Feng-Yi Ke (3 shared papers)Li‐Min Huang (3 shared papers)Woan‐Yuh Tarn (3 shared papers)Yi‐Ling Lin (2 shared papers)
- Journals
- Journal of Biomedical Science (6 papers)Pharmaceutics (1 paper)International Journal of Molecular Sciences (1 paper)Molecular Therapy — Nucleic Acids (1 paper)The Journal of Immunology (1 paper)
- Partner nations
- Taiwan
In The Last Decade
Shih-Han Ko
11 papers receiving 456 citations
Shih-Han Ko's Hit Papers
Peers
Comparison fields: 5 of 81
- Infectious Diseases 243
- Animal Science and Zoology 32
- Molecular Biology 216
- Immunology 66
- Cancer Research 32
Countries citing papers authored by Shih-Han Ko
This map shows the geographic impact of Shih-Han Ko'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-Han Ko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih-Han Ko more than expected).
Fields of papers citing papers by Shih-Han Ko
This network shows the impact of papers produced by Shih-Han Ko. 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-Han Ko. The network helps show where Shih-Han Ko may publish in the future.
Co-authors
The 25 scholars most cited alongside Shih-Han Ko, 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 | Monoclonal antibodies for COVID-19 therapy and SARS-CoV-2 detection Hit paper breakdown → | 2022 | 157 |
| 2 | 2022 | 94 | |
| 3 | 2013 | 62 | |
| 4 | 2021 | 44 | |
| 5 | 2024 | 34 | |
| 6 | 2021 | 18 | |
| 7 | 2019 | 18 | |
| 8 | 2021 | 17 | |
| 9 | 2018 | 13 | |
| 10 | 2022 | 7 | |
| 11 | 2025 | 1 | |
| 12 | 2025 | 0 |
About Shih-Han Ko
Shih-Han Ko is a scholar working on Infectious Diseases, Molecular Biology, Cardiology and Cardiovascular Medicine, Ecology and Genetics, having authored 12 papers that have together received 465 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), SARS-CoV-2 detection and testing (3 papers), COVID-19 Clinical Research Studies (3 papers), interferon and immune responses (2 papers), Bacteriophages and microbial interactions (2 papers), Virus-based gene therapy research (2 papers), RNA Interference and Gene Delivery (2 papers) and Viral gastroenteritis research and epidemiology (2 papers). The work is most often cited by research in Infectious Diseases (243 citations), Animal Science and Zoology (32 citations), Molecular Biology (216 citations), Immunology (66 citations) and Cancer Research (32 citations). Shih-Han Ko has collaborated with scholars based in Taiwan. Frequent co-authors include Han‐Chung Wu, Ruei‐Min Lu, Kang-Hao Liang, Shih-Chieh Su, Feng-Yi Ke, Li‐Min Huang, Woan‐Yuh Tarn, Yi‐Ling Lin, Chia-Yi Yu and Ching‐Len Liao. Their work appears in journals such as Journal of Biomedical Science, Pharmaceutics, International Journal of Molecular Sciences, Molecular Therapy — Nucleic Acids and The Journal of Immunology.
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.