Hao Lin
Impact in
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- Artificial Intelligence in Healthcare
- Molecular Biology top 10%
- Machine Learning in Bioinformatics
- RNA modifications and cancer
- Bioinformatics and Genomic Networks
Papers in
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- Gene expression and cancer classification 3
- Microbial metabolism and enzyme function 1
- Oncology 5
- Cancer Immunotherapy and Biomarkers 1
- Co-authors
- Fanny Dao (2 shared papers)Zimei Zhang (2 shared papers)Hui Qiong Yang (2 shared papers)Kejun Deng (3 shared papers)Zhao‐Yue Zhang (2 shared papers)Dan Yan (1 shared paper)Yamei Luo (1 shared paper)Hua Tang (1 shared paper)
- Journals
- IEEE Transactions on Antennas and Propagation (3 papers)Frontiers in Immunology (3 papers)Methods (2 papers)International Journal of Biological Macromolecules (2 papers)BMC Medical Genomics (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Hao Lin
37 papers receiving 907 citations
Peers
Comparison fields: 5 of 61
- Health Information Management 55
- Molecular Biology 360
- Cancer Research 56
- Hepatology 13
- Computational Theory and Mathematics 21
Countries citing papers authored by Hao Lin
This map shows the geographic impact of Hao Lin'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 Hao Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Lin more than expected).
Fields of papers citing papers by Hao Lin
This network shows the impact of papers produced by Hao Lin. 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 Hao Lin. The network helps show where Hao Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Hao Lin, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 190 | |
| 2 | 2021 | 152 | |
| 3 | 2020 | 86 | |
| 4 | 2015 | 74 | |
| 5 | 2020 | 44 | |
| 6 | 2022 | 44 | |
| 7 | 2019 | 40 | |
| 8 | 2023 | 39 | |
| 9 | 2021 | 38 | |
| 10 | 2024 | 38 | |
| 11 | 2021 | 27 | |
| 12 | 2022 | 27 | |
| 13 | 2022 | 18 | |
| 14 | 2022 | 15 | |
| 15 | 2019 | 13 | |
| 16 | 2020 | 10 | |
| 17 | 2020 | 9 | |
| 18 | 2022 | 6 | |
| 19 | 2023 | 6 | |
| 20 | 2021 | 5 |
About Hao Lin
Hao Lin is a scholar working on Molecular Biology, Oncology, Aerospace Engineering, Health Information Management and Immunology, having authored 40 papers that have together received 924 indexed citations. Recurring topics across this work include Antenna Design and Optimization (5 papers), Gene expression and cancer classification (3 papers), Atherosclerosis and Cardiovascular Diseases (3 papers), Artificial Intelligence in Healthcare (2 papers), MicroRNA in disease regulation (2 papers), Microbial metabolism and enzyme function (1 paper), Inflammatory Bowel Disease (1 paper) and Cancer Immunotherapy and Biomarkers (1 paper). The work is most often cited by research in Health Information Management (55 citations), Molecular Biology (360 citations), Cancer Research (56 citations), Hepatology (13 citations) and Computational Theory and Mathematics (21 citations). Hao Lin has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Fanny Dao, Zimei Zhang, Hui Qiong Yang, Kejun Deng, Zhao‐Yue Zhang, Dan Yan, Yamei Luo, Hua Tang, Xiaolin He and Ming Wu. Their work appears in journals such as IEEE Transactions on Antennas and Propagation, Frontiers in Immunology, Methods, International Journal of Biological Macromolecules and BMC Medical Genomics.
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.