Dan Jin
Impact in
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- Immune Cell Function and Interaction
- Immune cells in cancer
Papers in
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- Circular RNAs in diseases 2
- RNA Research and Splicing 2
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- Microtubule and mitosis dynamics 3
- Co-authors
- Su Fu (3 shared papers)Jingjing Xie (2 shared papers)Qunyi Guo (2 shared papers)Dianshuai Gao (3 shared papers)Ziyi Xu (2 shared papers)Jianqun Wu (2 shared papers)Song Liu (2 shared papers)Yao Xiao (1 shared paper)
- Journals
- Journal of Cellular Physiology (2 papers)Hepatology (1 paper)BioMed Research International (1 paper)Cancer Cell International (1 paper)Neuropeptides (1 paper)
- Partner nations
- ChinaSouth KoreaUnited Kingdom
In The Last Decade
Dan Jin
21 papers receiving 538 citations
Peers
Comparison fields: 5 of 102
- Cancer Research 95
- Immunology 78
- Cellular and Molecular Neuroscience 56
- Molecular Biology 203
- Oncology 72
Countries citing papers authored by Dan Jin
This map shows the geographic impact of Dan Jin'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 Dan Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Jin more than expected).
Fields of papers citing papers by Dan Jin
This network shows the impact of papers produced by Dan Jin. 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 Dan Jin. The network helps show where Dan Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Jin, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 82 | |
| 2 | 2009 | 63 | |
| 3 | 2012 | 51 | |
| 4 | 2015 | 51 | |
| 5 | 2014 | 50 | |
| 6 | 2018 | 38 | |
| 7 | 2019 | 30 | |
| 8 | 2018 | 26 | |
| 9 | 2022 | 21 | |
| 10 | 2015 | 20 | |
| 11 | 2019 | 20 | |
| 12 | 2018 | 20 | |
| 13 | 2023 | 18 | |
| 14 | 2019 | 15 | |
| 15 | 2017 | 14 | |
| 16 | 2016 | 10 | |
| 17 | 2020 | 4 | |
| 18 | 2025 | 3 | |
| 19 | 2011 | 2 | |
| 20 | 2007 | 1 |
About Dan Jin
Dan Jin is a scholar working on Molecular Biology, Cell Biology, Electrical and Electronic Engineering, Cancer Research and Cellular and Molecular Neuroscience, having authored 22 papers that have together received 540 indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (3 papers), Axon Guidance and Neuronal Signaling (3 papers), Neuropeptides and Animal Physiology (3 papers), Cancer-related molecular mechanisms research (3 papers), Glioma Diagnosis and Treatment (2 papers), Circular RNAs in diseases (2 papers), RNA Research and Splicing (2 papers) and Cancer Mechanisms and Therapy (2 papers). The work is most often cited by research in Cancer Research (95 citations), Immunology (78 citations), Cellular and Molecular Neuroscience (56 citations), Molecular Biology (203 citations) and Oncology (72 citations). Dan Jin has collaborated with scholars based in China, South Korea and United Kingdom. Frequent co-authors include Su Fu, Jingjing Xie, Qunyi Guo, Dianshuai Gao, Ziyi Xu, Jianqun Wu, Song Liu, Yao Xiao, Jianhong Li and Xufeng Qi. Their work appears in journals such as Journal of Cellular Physiology, Hepatology, BioMed Research International, Cancer Cell International and Neuropeptides.
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.