Kan Chen

1.1k citations
33 papers · 636 · h-index 16

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Galectins and Cancer Biology

Papers in

    • Circular RNAs in diseases 5
    • Protein Tyrosine Phosphatases 5
    • Sphingolipid Metabolism and Signaling 3
    • MicroRNA in disease regulation 6

Kan Chen

32 papers receiving 632 citations

Peers

Kan Chen
Comparison fields: 5 of 89
  • Cancer Research 136
  • Immunology 133
  • Hepatology 49
  • Molecular Biology 359
  • Biochemistry 32
Replace Sung Hee Hong with:
Sung Hee Hong South Korea
Gyrid Nygaard Norway
Manabu Iwadate Japan
Jinghan Zhu China
Zheng Cui United States
Xiuling Li China
Dongxian Guan China
Dalila Marques United States
Qiong Shi China
Kan Chen relative to Sung Hee Hong South Korea Sung Hee Hong's profile →
Citations per field
00.5×2.9×
Sung Hee Hong · 1×
Citations per year

Countries citing papers authored by Kan Chen

Since Specialization
Citations

This map shows the geographic impact of Kan Chen'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 Kan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kan Chen more than expected).

Fields of papers citing papers by Kan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kan Chen. 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 Kan Chen. The network helps show where Kan Chen may publish in the future.

Co-authors

The 25 scholars most cited alongside Kan Chen, 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 Kan Chen Line = papers co-authored together Kan Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201794
2 201662
3 201536
4 201735
5 201932
6 202232
7 201531
8 200930
9 201925
10 201324
11 202423
12 201323
13 201922
14 201421
15 201820
16
Resveratrol inhibits dysfunction of dendritic cells from chronic obstructive pulmonary disease patients through promoting miR-34.
201516
17 201915
18 201713
19 202412
20 202111

About Kan Chen

Kan Chen is a scholar working on Molecular Biology, Cancer Research, Cell Biology, Spectroscopy and Oncology, having authored 33 papers that have together received 636 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (6 papers), Circular RNAs in diseases (5 papers), Protein Tyrosine Phosphatases (5 papers), Molecular Sensors and Ion Detection (4 papers), Cancer Cells and Metastasis (3 papers), Sphingolipid Metabolism and Signaling (3 papers), Sulfur Compounds in Biology (3 papers) and Zebrafish Biomedical Research Applications (3 papers). The work is most often cited by research in Cancer Research (136 citations), Immunology (133 citations), Hepatology (49 citations), Molecular Biology (359 citations) and Biochemistry (32 citations). Kan Chen has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Changqian Wang, Zhihua Han, Lin Gao, Jiatian Cao, Siying Wang, Yue Wang, Yuqi Fan, Fan Yang, Maikel P. Peppelenbosch and Yuqi Fan. Their work appears in journals such as Drug Design Development and Therapy, Cancer Cell International, Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Helicobacter and Journal of Nanoparticle 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.

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