Hao Lin
- Molecular Biology top 0.1%
- Machine Learning in Bioinformatics 147
- RNA and protein synthesis mechanisms 122
- Genomics and Phylogenetic Studies 98
- RNA modifications and cancer 23
- vaccines and immunoinformatics approaches 16
- Genomics and Chromatin Dynamics 12
- Microbiology top 0.5%
- Cancer Research top 1%
- Cancer-related molecular mechanisms research 19
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods 19
- Urology top 1%
- Journals
- Briefings in Bioinformatics (17 papers)Bioinformatics (13 papers)International Journal of Molecular Sciences (10 papers)
- Partner nations
- ChinaUnited StatesSaudi Arabia
In The Last Decade
Hao Lin
299 papers receiving 20.4k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Molecular Biology 15.4k
- Microbiology 833
- Cancer Research 1.6k
- Computational Theory and Mathematics 1.6k
- Urology 378
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 8 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 21 | |
| 6 | 2024 | 13 | |
| 7 | 2024 | 18 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 72 | |
| 11 | 2023 | 8 | |
| 12 | 2022 | 27 | |
| 13 | 2021 | 8 | |
| 14 | 2020 | 2 | |
| 15 | 2018 | 161 | |
| 16 | 2016 | 49 | |
| 17 | 2016 | 18 | |
| 18 | 2015 | 278 | |
| 19 | 2014 | 103 | |
| 20 | 2014 | 156 |
About Hao Lin
Hao Lin is a scholar working on Molecular Biology, Cancer Research, Microbiology, Computational Theory and Mathematics and Biological Psychiatry, having authored 311 papers that have together received 20.6k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (147 papers), RNA and protein synthesis mechanisms (122 papers), Genomics and Phylogenetic Studies (98 papers), RNA modifications and cancer (23 papers), Computational Drug Discovery Methods (19 papers), Cancer-related molecular mechanisms research (19 papers), vaccines and immunoinformatics approaches (16 papers) and Genomics and Chromatin Dynamics (12 papers). The work is most often cited by research in Molecular Biology (15.4k citations), Microbiology (833 citations), Cancer Research (1.6k citations), Computational Theory and Mathematics (1.6k citations) and Urology (378 citations). Hao Lin has collaborated with scholars based in China, United States and Saudi Arabia. Frequent co-authors include Wei Chen, Hui Ding, Kuo‐Chen Chou, Pengmian Feng, Zhenduo Shi, Conghui Han, Gang Wang, Yang Dong, Zhiguo Zhang and Hua Tang. Their work appears in journals such as Briefings in Bioinformatics, Bioinformatics, International Journal of Molecular Sciences, Scientific Reports and Molecular Therapy — Nucleic Acids.
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.