Sheng‐Da Hsu
- Molecular Biology top 2%
- Cancer Research top 0.5%
- Epidemiology top 10%
- Immunology top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Hsien‐Da HuangFeng‐Mao LinAnn‐Ping TsouHsi‐Yuan HuangChih‐Hung ChouChih-Min ChiuChia-Hung ChienSirjana Shrestha
- Topics
- MicroRNA in disease regulation (12 papers)Cancer-related molecular mechanisms research (9 papers)RNA Research and Splicing (7 papers)
- Partner nations
- TaiwanUnited StatesGermany
In The Last Decade
Sheng‐Da Hsu
18 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Molecular Biology 3.2k
- Cancer Research 2.8k
- Epidemiology 273
- Immunology 245
- Pulmonary and Respiratory Medicine 174
Countries citing papers authored by Sheng‐Da Hsu
This map shows the geographic impact of Sheng‐Da Hsu'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 Sheng‐Da Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng‐Da Hsu more than expected).
Fields of papers citing papers by Sheng‐Da Hsu
This network shows the impact of papers produced by Sheng‐Da Hsu. 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 Sheng‐Da Hsu. The network helps show where Sheng‐Da Hsu may publish in the future.
Co-authorship network of co-authors of Sheng‐Da Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Sheng‐Da Hsu. A scholar is included among the top collaborators of Sheng‐Da Hsu 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 Sheng‐Da Hsu. Sheng‐Da Hsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 6 | |
| 3 | 34 | |
| 4 | 39 | |
| 5 | 7 | |
| 6 | 280 | |
| 7 | 31 | |
| 8 | 118 | |
| 9 | 233 | |
| 10 | 8 | |
| 11 | miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactionsbreakdown → | 892 |
| 12 | 91 | |
| 13 | MicroRNA-122 plays a critical role in liver homeostasis and hepatocarcinogenesisbreakdown → | 670 |
| 14 | 95 | |
| 15 | 115 | |
| 16 | miRTarBase: a database curates experimentally validated microRNA–target interactionsbreakdown → | 1074 |
| 17 | 223 | |
| 18 | 85 |
About Sheng‐Da Hsu
Sheng‐Da Hsu is a scholar working on Cancer Research, Hepatology and Physiology, having authored 18 papers that have together received 4.0k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (12 papers), Cancer-related molecular mechanisms research (9 papers) and RNA Research and Splicing (7 papers). The work is most often cited by research in Cancer Research (2.8k citations), Molecular Biology (3.2k citations) and Hepatology (159 citations). Sheng‐Da Hsu has collaborated with scholars based in Taiwan, United States and Germany. Frequent co-authors include Hsien‐Da Huang, Feng‐Mao Lin, Ann‐Ping Tsou, Hsi‐Yuan Huang, Chih‐Hung Chou, Chih-Min Chiu, Chia-Hung Chien, Sirjana Shrestha, Weiyun Wu and Chi‐Ying F. Huang. Their work appears in journals such as Nucleic Acids Research, Journal of Clinical Investigation and Journal of Virology.
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.