Kun Lin
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
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- Circular RNAs in diseases
- Extracellular vesicles in disease
- RNA modifications and cancer
Papers in
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- Circular RNAs in diseases 5
- RNA modifications and cancer 3
- Extracellular vesicles in disease 2
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- MicroRNA in disease regulation 8
- Cancer-related molecular mechanisms research 8
- Co-authors
- Shu‐Qiang Zhu (6 shared papers)Bai‐Quan Qiu (6 shared papers)Xiang Long (6 shared papers)Feng Lü (6 shared papers)Yongbing Wu (5 shared papers)Xu Pei (5 shared papers)Shiwei Chen (3 shared papers)Jianjun Xu (5 shared papers)
- Journals
- Aging (2 papers)Annals of Translational Medicine (2 papers)Molecular Cancer (2 papers)Analytical and Bioanalytical Chemistry (1 paper)Epilepsy Research (1 paper)
- Partner nations
- China
In The Last Decade
Kun Lin
24 papers receiving 620 citations
Peers
Comparison fields: 5 of 73
- Cancer Research 347
- Molecular Biology 470
- Immunology 82
- Pulmonary and Respiratory Medicine 87
- Oncology 71
Countries citing papers authored by Kun Lin
This map shows the geographic impact of Kun 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 Kun Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Lin more than expected).
Fields of papers citing papers by Kun Lin
This network shows the impact of papers produced by Kun 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 Kun Lin. The network helps show where Kun Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 199 | |
| 2 | 2022 | 88 | |
| 3 | 2020 | 60 | |
| 4 | 2020 | 53 | |
| 5 | 2018 | 43 | |
| 6 | 2021 | 32 | |
| 7 | 2019 | 22 | |
| 8 | 2020 | 15 | |
| 9 | 2021 | 14 | |
| 10 | 2018 | 14 | |
| 11 | 2022 | 14 | |
| 12 | 2018 | 11 | |
| 13 | 2015 | 10 | |
| 14 | 2021 | 9 | |
| 15 | 2022 | 8 | |
| 16 | 2023 | 8 | |
| 17 | Identification of potential key autophagy-related genes in asthma with bioinformatics approaches. | 2022 | 8 |
| 18 | 2020 | 6 | |
| 19 | 2018 | 4 | |
| 20 | 2017 | 4 |
About Kun Lin
Kun Lin is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Genetics and Physiology, having authored 25 papers that have together received 626 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (8 papers), Cancer-related molecular mechanisms research (8 papers), Circular RNAs in diseases (5 papers), Glioma Diagnosis and Treatment (4 papers), RNA modifications and cancer (3 papers), Ferroptosis and cancer prognosis (2 papers), Asthma and respiratory diseases (2 papers) and Extracellular vesicles in disease (2 papers). The work is most often cited by research in Cancer Research (347 citations), Molecular Biology (470 citations), Immunology (82 citations), Pulmonary and Respiratory Medicine (87 citations) and Oncology (71 citations). Kun Lin has collaborated with scholars based in China. Frequent co-authors include Shu‐Qiang Zhu, Bai‐Quan Qiu, Xiang Long, Feng Lü, Yongbing Wu, Xu Pei, Shiwei Chen, Jianjun Xu, Dian Xiong and Pengfei Zhang. Their work appears in journals such as Aging, Annals of Translational Medicine, Molecular Cancer, Analytical and Bioanalytical Chemistry and Epilepsy Research.
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.