Kun Yan

403 citations
12 papers · 344 · h-index 9

Impact in

    • Cancer, Hypoxia, and Metabolism
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Cancer Immunotherapy and Biomarkers
    • Metal complexes synthesis and properties
    • Cytokine Signaling Pathways and Interactions

Papers in

    • Cytokine Signaling Pathways and Interactions 2
    • Peptidase Inhibition and Analysis 1
    • Cancer-related molecular mechanisms research 2
    • MicroRNA in disease regulation 2

Kun Yan

12 papers receiving 342 citations

Peers

Kun Yan
Comparison fields: 5 of 69
  • Cancer Research 119
  • Oncology 83
  • Molecular Biology 149
  • Immunology 43
  • Pulmonary and Respiratory Medicine 40
Replace Dannah R. Miller with:
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Anli Jin China
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Citations per field
00.5×2×3×4×5×
Dannah R. Miller · 1×
Citations per year

Countries citing papers authored by Kun Yan

Since Specialization
Citations

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

Fields of papers citing papers by Kun Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 201283
2 201660
3 201954
4 201935
5 201230
6
Modified glasgow prognostic score as a prognostic factor in gastriccancer patients: a systematic review and meta-analysis.
201519
7 200919
8 201817
9 201711
10 20209
11 20196
12 20191

About Kun Yan

Kun Yan is a scholar working on Oncology, Cancer Research, Toxicology, Immunology and Immunology and Allergy, having authored 12 papers that have together received 344 indexed citations. Recurring topics across this work include interferon and immune responses (2 papers), Circular RNAs in diseases (2 papers), Cancer-related molecular mechanisms research (2 papers), Cytokine Signaling Pathways and Interactions (2 papers), MicroRNA in disease regulation (2 papers), Cancer Mechanisms and Therapy (1 paper), Peptidase Inhibition and Analysis (1 paper) and Cell Adhesion Molecules Research (1 paper). The work is most often cited by research in Cancer Research (119 citations), Oncology (83 citations), Molecular Biology (149 citations), Immunology (43 citations) and Pulmonary and Respiratory Medicine (40 citations). Kun Yan has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Ji Zongzheng, Xin Xu, Wei Cheng, Chengxue Dang, Huafeng Kang, Yanxia Huang, Xiaobin Ma, Jie Li, Yiming Li and Haitao Guan. Their work appears in journals such as Biochemical and Biophysical Research Communications, Molecular Immunology, Oncology Reports, Chemical Science and Journal of Experimental & Clinical Cancer 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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