Kun Chen

5.3k citations
189 papers · 3.8k indexed · h-index 31
Topics
Cancer-related molecular mechanisms research (27 papers)Bone Metabolism and Diseases (17 papers)RNA modifications and cancer (11 papers)
Partner nations
ChinaUnited StatesCanada

In The Last Decade

Kun Chen

181 papers receiving 3.7k citations

Peers

Kun Chen
Comparison fields: 5 of 165
  • Molecular Biology 1.7k
  • Cancer Research 685
  • Immunology 494
  • Oncology 402
  • Epidemiology 398
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Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by Kun Chen

Since Specialization
Citations

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

Fields of papers citing papers by Kun Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Chen. A scholar is included among the top collaborators of Kun Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kun Chen. Kun Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 9
2 1
3 5
4 16
5 1
6 8
7 1
8 11
9 3
10 46
11
MiR-1224-5p Activates Autophagy, Cell Invasion and Inhibits Epithelial-to-Mesenchymal Transition in Osteosarcoma Cells by Directly Targeting PLK1 Through PI3K/AKT/mTOR Signaling Pathway
1
12
LncRNA OR3A4 Regulated the Growth of Osteosarcoma Cells by Modulating the miR-1207-5p/G6PD Signaling
2
13
A Fusion Deep Convolutional Neural Network Based on Pathological Features for Diagnosing Plus Disease in Retinopathy of Prematurity
1
14 22
15 3
16 8
17
Adenovirus vector expressing mda-7 selectively kills hepatocellular carcinoma cell line Hep3B.
5
18
[Inhibition of hepatocellular carcinoma growth by adenovirus-mediated mda-7 with adriamycin].
2
19
[Adenovirus vector expressing MDA-7/IL-24 selectively induces growth arrests and apoptosis in human hepatocellular carcinoma cell lines independent of the state of p53 gene].
3
20
[A case-control study on the relationship between nutrition and gastric cancer in islanders].
2

About Kun Chen

Kun Chen is a scholar working on Cancer Research, Molecular Biology and Endocrinology, having authored 189 papers that have together received 3.8k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (27 papers), Bone Metabolism and Diseases (17 papers) and RNA modifications and cancer (11 papers). The work is most often cited by research in Cancer Research (685 citations), Molecular Biology (1.7k citations) and Immunology (494 citations). Kun Chen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Peng Wang, Ling Qian, Yalei Zhang, Michael J. Morgan, Zheng-gang Liu, Swati Choksi, Yan Zhang, Jason Maley, Xuetao Cao and Peter H. Yu. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

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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