Dan Jin

919 citations
22 papers · 525 · h-index 14

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Immune Cell Function and Interaction
    • Immune Response and Inflammation
    • Immune cells in cancer

Papers in

Dan Jin

20 papers receiving 523 citations

Peers

Dan Jin
Comparison fields: 5 of 104
  • Cancer Research 114
  • Immunology 92
  • Molecular Biology 236
  • Cellular and Molecular Neuroscience 60
  • Hepatology 25
Replace Tong Yu with:
Tong Yu China
Jun Sun China
Danielle E. White United Kingdom
Taghrid B. El-Abaseri Egypt
Xiaobo Zhang China
Panida Lertkiatmongkol United States
Jingping Zhou China
Dong Guo China
Dan Jin relative to Tong Yu China Tong Yu's profile →
Citations per field
00.5×6.3×
Tong Yu · 1×
Citations per year

Countries citing papers authored by Dan Jin

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Dan Jin Line = papers co-authored together Dan Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201979
2 200962
3 201551
4 201251
5 201450
6 201838
7 201930
8 201826
9 201920
10 201519
11 201819
12 202218
13 202316
14 201915
15 201713
16 201610
17 20204
18 20112
19 20071
20 20221

About Dan Jin

Dan Jin is a scholar working on Molecular Biology, Cell Biology, Electrical and Electronic Engineering, Cancer Research and Pathology and Forensic Medicine, having authored 22 papers that have together received 525 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (3 papers), Cancer-related molecular mechanisms research (3 papers), Microtubule and mitosis dynamics (3 papers), Axon Guidance and Neuronal Signaling (3 papers), Cytokine Signaling Pathways and Interactions (2 papers), MicroRNA in disease regulation (2 papers), RNA Research and Splicing (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Cancer Research (114 citations), Immunology (92 citations), Molecular Biology (236 citations), Cellular and Molecular Neuroscience (60 citations) and Hepatology (25 citations). Dan Jin has collaborated with scholars based in China, South Korea and United Kingdom. Frequent co-authors include Su Fu, Qunyi Guo, Jingjing Xie, Dianshuai Gao, Ziyi Xu, Chao Qu, Kyu‐Jae Lee, Xufeng Qi, Fangfang Li and Jianhong Li. Their work appears in journals such as Journal of Cellular Physiology, Molecular Pharmaceutics, Neuropeptides, Solar Energy and Advanced Healthcare Materials.

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.

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