Sai Hu
Impact in
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- DNA Repair Mechanisms
- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- Gut microbiota and health
- Ubiquitin and proteasome pathways
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- Effects of Radiation Exposure
Papers in
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- Bioinformatics and Genomic Networks 14
- Machine Learning in Bioinformatics 12
- DNA Repair Mechanisms 3
- Microbial Metabolic Engineering and Bioproduction 2
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- Computational Drug Discovery Methods 8
- Co-authors
- Ping‐Kun Zhou (13 shared papers)Yao Zhou (6 shared papers)Ruixue Huang (6 shared papers)Bihai Zhao (15 shared papers)Hua Guan (5 shared papers)Chenjun Bai (3 shared papers)Fengmei Cui (1 shared paper)Guofeng Ren (1 shared paper)
- Journals
- BMC Bioinformatics (3 papers)Human Genomics (2 papers)Frontiers in Genetics (2 papers)Scientific Reports (1 paper)Molecular Therapy — Oncolytics (1 paper)
- Partner nations
- China
In The Last Decade
Sai Hu
31 papers receiving 325 citations
Peers
Comparison fields: 5 of 81
- Molecular Biology 205
- Radiology, Nuclear Medicine and Imaging 59
- Cancer Research 35
- Oncology 63
- Pulmonary and Respiratory Medicine 58
Countries citing papers authored by Sai Hu
This map shows the geographic impact of Sai Hu'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 Sai Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sai Hu more than expected).
Fields of papers citing papers by Sai Hu
This network shows the impact of papers produced by Sai Hu. 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 Sai Hu. The network helps show where Sai Hu may publish in the future.
Co-authors
The 25 scholars most cited alongside Sai Hu, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 40 | |
| 2 | 2019 | 36 | |
| 3 | 2020 | 32 | |
| 4 | 2020 | 25 | |
| 5 | 2019 | 24 | |
| 6 | 2020 | 24 | |
| 7 | 2016 | 20 | |
| 8 | 2020 | 18 | |
| 9 | 2020 | 16 | |
| 10 | 2020 | 15 | |
| 11 | 2020 | 11 | |
| 12 | 2020 | 8 | |
| 13 | 2020 | 7 | |
| 14 | 2019 | 7 | |
| 15 | 2022 | 6 | |
| 16 | 2020 | 6 | |
| 17 | 2021 | 5 | |
| 18 | 2024 | 5 | |
| 19 | 2022 | 4 | |
| 20 | 2024 | 4 |
About Sai Hu
Sai Hu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pulmonary and Respiratory Medicine, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 35 papers that have together received 332 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (14 papers), Machine Learning in Bioinformatics (12 papers), Computational Drug Discovery Methods (8 papers), Effects of Radiation Exposure (4 papers), DNA Repair Mechanisms (3 papers), MicroRNA in disease regulation (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Molecular Biology (205 citations), Radiology, Nuclear Medicine and Imaging (59 citations), Cancer Research (35 citations), Oncology (63 citations) and Pulmonary and Respiratory Medicine (58 citations). Sai Hu has collaborated with scholars based in China. Frequent co-authors include Ping‐Kun Zhou, Yao Zhou, Ruixue Huang, Bihai Zhao, Hua Guan, Chenjun Bai, Fengmei Cui, Guofeng Ren, Yongqing Gu and Han Yang. Their work appears in journals such as BMC Bioinformatics, Human Genomics, Frontiers in Genetics, Scientific Reports and Molecular Therapy — Oncolytics.
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.