Dan Jin
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Pharmacology top 5%
- Cannabis and Cannabinoid Research
- Medicinal Plant Pharmacodynamics Research
Papers in
-
- Wnt/β-catenin signaling in development and cancer 5
- Bone Metabolism and Diseases 4
- Cancer-related gene regulation 4
-
- GABA and Rice Research 4
- Co-authors
- Jie Chen (4 shared papers)Joanne Durgan (4 shared papers)Alan Hall (4 shared papers)Carol A. Gross (1 shared paper)Juanjuan Dai (2 shared papers)Kaikai Gong (2 shared papers)Jing Du (2 shared papers)Yan Wu (2 shared papers)
- Journals
- Molecular and Cellular Endocrinology (3 papers)Journal of Biological Chemistry (3 papers)Medicine (2 papers)Frontiers in Pharmacology (2 papers)Frontiers in Plant Science (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Dan Jin
77 papers receiving 2.4k citations
Dan Jin's Hit Papers
Peers
Comparison fields: 5 of 130
- Cancer Research 302
- Pharmacology 319
- Molecular Biology 1.1k
- Pharmacology 126
- Toxicology 42
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 80 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 274 | |
| 2 | Secondary Metabolites Profiled in Cannabis Inflorescences, Leaves, Stem Barks, and Roots for Medicinal Purposes Hit paper breakdown → | 2020 | 256 |
| 3 | 2011 | 115 | |
| 4 | 2011 | 92 | |
| 5 | 2018 | 88 | |
| 6 | 2014 | 74 | |
| 7 | 1991 | 74 | |
| 8 | 2019 | 68 | |
| 9 | 2015 | 64 | |
| 10 | 2022 | 62 | |
| 11 | 2021 | 60 | |
| 12 | 2010 | 57 | |
| 13 | 2013 | 54 | |
| 14 | 2019 | 49 | |
| 15 | 2018 | 49 | |
| 16 | 2014 | 48 | |
| 17 | 2010 | 46 | |
| 18 | 2021 | 44 | |
| 19 | 2011 | 44 | |
| 20 | 2014 | 41 |
About Dan Jin
Dan Jin is a scholar working on Molecular Biology, Plant Science, Surgery, Pharmacology and Epidemiology, having authored 80 papers that have together received 2.4k indexed citations. Recurring topics across this work include Cannabis and Cannabinoid Research (6 papers), Adipose Tissue and Metabolism (5 papers), Wnt/β-catenin signaling in development and cancer (5 papers), GABA and Rice Research (4 papers), Bone Metabolism and Diseases (4 papers), Autophagy in Disease and Therapy (4 papers), Cancer-related gene regulation (4 papers) and MicroRNA in disease regulation (4 papers). The work is most often cited by research in Cancer Research (302 citations), Pharmacology (319 citations), Molecular Biology (1.1k citations), Pharmacology (126 citations) and Toxicology (42 citations). Dan Jin has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Jie Chen, Joanne Durgan, Alan Hall, Carol A. Gross, Juanjuan Dai, Kaikai Gong, Jing Du, Yan Wu, Jiwei Guo and Shuang Miao. Their work appears in journals such as Molecular and Cellular Endocrinology, Journal of Biological Chemistry, Medicine, Frontiers in Pharmacology and Frontiers in Plant Science.
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.