Li Hsu
- Genetics top 2%
- Molecular Biology
- Statistics and Probability top 1%
- Cancer Research top 10%
- Oncology top 10%
- Co-authors
- Malka GorfineBarbara J. TraskLue Ping ZhaoHillary F. MassaJanet M. YoungKathleen E. MaloneYingye ZhengJianping Sun
- Topics
- Genetic Associations and Epidemiology (48 papers)Statistical Methods and Inference (28 papers)Gene expression and cancer classification (17 papers)
- Journals
- Nature GeneticsJournal of Clinical OncologySHILAP Revista de lepidopterología
- Partner nations
- United StatesIsraelSouth Africa
In The Last Decade
Li Hsu
113 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 131
- Genetics 796
- Molecular Biology 663
- Statistics and Probability 448
- Cancer Research 291
- Oncology 266
Countries citing papers authored by Li Hsu
This map shows the geographic impact of Li 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 Li Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Hsu more than expected).
Fields of papers citing papers by Li Hsu
This network shows the impact of papers produced by Li 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 Li Hsu. The network helps show where Li Hsu may publish in the future.
Co-authorship network of co-authors of Li Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Li Hsu. A scholar is included among the top collaborators of Li 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 Li Hsu. Li 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 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | 29 | |
| 7 | Bootstrap Inference for Network Construction | 9 |
| 8 | 4 | |
| 9 | 51 | |
| 10 | 46 | |
| 11 | 46 | |
| 12 | 3 | |
| 13 | Identification of genomic alterations differentiating lobular and ductal subtypes of breast cancer | 2 |
| 14 | 4 | |
| 15 | 173 | |
| 16 | 10 | |
| 17 | 6 | |
| 18 | 8 | |
| 19 | 8 | |
| 20 | COMPARATIVE STUDIES ON THE INFECTION AND MATURATION OF SCHISTOSOMA JAPONICUM IN CATTLE AND BUFFALOES | 6 |
About Li Hsu
Li Hsu is a scholar working on Statistics and Probability, Genetics and Pathology and Forensic Medicine, having authored 120 papers that have together received 2.1k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (48 papers), Statistical Methods and Inference (28 papers) and Gene expression and cancer classification (17 papers). The work is most often cited by research in Statistics and Probability (448 citations), Genetics (796 citations) and Cancer Research (291 citations). Li Hsu has collaborated with scholars based in United States, Israel and South Africa. Frequent co-authors include Malka Gorfine, Barbara J. Trask, Lue Ping Zhao, Hillary F. Massa, Janet M. Young, Kathleen E. Malone, Yingye Zheng, Jianping Sun, Charles Kooperberg and David M. Zucker. Their work appears in journals such as Nature Genetics, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.