Lin Gao
- Cancer Research top 2%
- MicroRNA in disease regulation 11
- Cancer-related molecular mechanisms research 11
- Molecular Biology top 5%
- RNA modifications and cancer 7
- Metabolism, Diabetes, and Cancer 6
- Circular RNAs in diseases 6
- Developmental Neuroscience top 10%
- Biochemistry top 5%
- Immunology top 10%
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- Adipose Tissue and Metabolism 9
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- Catalytic Processes in Materials Science 8
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- Nerve injury and regeneration 5
- Journals
- Proceedings of the National Academy of Sciences (1 paper)SHILAP Revista de lepidopterología (2 papers)Environmental Science & Technology (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Lin Gao
132 papers receiving 3.4k citations
Peers
Comparison fields: 5 of 139
- Cancer Research 765
- Molecular Biology 1.8k
- Developmental Neuroscience 70
- Biochemistry 110
- Immunology 274
Countries citing papers authored by Lin Gao
This map shows the geographic impact of Lin Gao'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 Lin Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Gao more than expected).
Fields of papers citing papers by Lin Gao
This network shows the impact of papers produced by Lin Gao. 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 Lin Gao. The network helps show where Lin Gao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Lin Gao, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 7 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2021 | 1 | |
| 12 | 2021 | 4 | |
| 13 | 2020 | 144 | |
| 14 | 2019 | 22 | |
| 15 | 2018 | 70 | |
| 16 | 2018 | 40 | |
| 17 | Heparanase promotes human gastric cancer cells migration and invasion by increasing Src and p38 phosphorylation expression. | 2014 | 12 |
| 18 | 2012 | 87 | |
| 19 | 2012 | 1 | |
| 20 | DNA Algorithm to the Directed Shortest Hamilton Path Problem | 2002 | 3 |
About Lin Gao
Lin Gao is a scholar working on Cancer Research, Molecular Biology and Biochemistry, having authored 140 papers that have together received 3.5k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (11 papers), Cancer-related molecular mechanisms research (11 papers), Adipose Tissue and Metabolism (9 papers), Catalytic Processes in Materials Science (8 papers), RNA modifications and cancer (7 papers), Metabolism, Diabetes, and Cancer (6 papers), Circular RNAs in diseases (6 papers) and Nerve injury and regeneration (5 papers). The work is most often cited by research in Cancer Research (765 citations), Molecular Biology (1.8k citations) and Developmental Neuroscience (70 citations). Lin Gao has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Changqian Wang, Xiaoning Zeng, Yi Fan, Xiu‐Lan Sun, Gang Hu, Jianhua Ding, Zhihua Han, Zheng‐Xiang Li, Gangyi Yang and Jin Zhao. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Environmental Science & Technology.
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.