Kun Shi

1.9k total citations · 1 hit paper
39 papers, 1.3k citations indexed

About

Kun Shi is a scholar working on Molecular Biology, Surgery and Immunology. According to data from OpenAlex, Kun Shi has authored 39 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 10 papers in Surgery and 7 papers in Immunology. Recurrent topics in Kun Shi's work include Protein Tyrosine Phosphatases (5 papers), Galectins and Cancer Biology (5 papers) and Biochemical and Molecular Research (4 papers). Kun Shi is often cited by papers focused on Protein Tyrosine Phosphatases (5 papers), Galectins and Cancer Biology (5 papers) and Biochemical and Molecular Research (4 papers). Kun Shi collaborates with scholars based in China, Japan and Canada. Kun Shi's co-authors include Albert M. Berghuis, Katsuya Egawa, Hiroshi Maegawa, Atsunori Kashiwagi, Takeshi Yoshizaki, Satoshi Ugi, Toshiyuki Obata, Yanju Liu, Jerrold M. Olefsky and Takeshi Imamura and has published in prestigious journals such as Journal of Biological Chemistry, Molecular and Cellular Biology and Biochemistry.

In The Last Decade

Kun Shi

35 papers receiving 1.2k citations

Hit Papers

A Chemoproteomic Approach to Query the Degradable Kinome ... 2017 2026 2020 2023 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Chemoproteomic Approach to Query the Degradable Kinome Using a Multi-kinase Degrader
    2017 330 citations Hai‐Tsang Huang, Joshiawa Paulk et al. Cell chemical biology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kun Shi China 19 940 193 112 109 104 39 1.3k
Rit Vatsyayan United States 22 634 0.7× 178 0.9× 87 0.8× 60 0.6× 57 0.5× 33 1.1k
Xiao-bo Zhong United States 12 567 0.6× 274 1.4× 139 1.2× 128 1.2× 116 1.1× 13 1.3k
Dean Gilham United States 20 774 0.8× 134 0.7× 191 1.7× 114 1.0× 310 3.0× 39 1.4k
Laura Cesaratto Italy 18 910 1.0× 191 1.0× 124 1.1× 30 0.3× 85 0.8× 25 1.3k
Yu Gu China 21 778 0.8× 108 0.6× 215 1.9× 159 1.5× 98 0.9× 61 1.3k
Aoli Wang China 18 1.5k 1.6× 177 0.9× 111 1.0× 132 1.2× 198 1.9× 60 1.9k
Sabine M. Klauck Germany 20 955 1.0× 171 0.9× 160 1.4× 67 0.6× 109 1.0× 58 1.6k
Jiyeon Ahn South Korea 22 830 0.9× 197 1.0× 88 0.8× 40 0.4× 69 0.7× 56 1.4k
Hongmei Luo China 19 587 0.6× 130 0.7× 95 0.8× 59 0.5× 45 0.4× 73 1.3k
Dipak Panigrahy United States 15 404 0.4× 186 1.0× 89 0.8× 63 0.6× 132 1.3× 30 1.3k

Countries citing papers authored by Kun Shi

Since Specialization
Citations

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

Fields of papers citing papers by Kun Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Shi. A scholar is included among the top collaborators of Kun Shi 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 Shi. Kun Shi 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
1.
Su, Faye, Chengcheng Liu, Zehui Lv, et al.. (2025). Global research trends in artificial intelligence in cardiovascular medicine: A bibliometric analysis. Archives of cardiovascular diseases. 119(2). 162–175.
2.
3.
Shi, Kun, Bin Wu, Jiyuan Tu, et al.. (2024). Mechanism of Shenfu Injection in Treating Ischemic Stroke Elucidated using Network Pharmacology and Experimental Validation. Current Computer - Aided Drug Design. 21(6). 793–806.
4.
Shi, Kun, et al.. (2024). Atractylodin modulates ASAH3L to improve galactose metabolism and inflammation to alleviate acute lung injury. iScience. 27(10). 110751–110751. 3 indexed citations
5.
Shi, Kun, Yan Wang, Jiyuan Tu, et al.. (2023). Therapeutic effects and mechanism of Atractylodis rhizoma in acute lung injury: Investigation based on an Integrated approach. Frontiers in Pharmacology. 14. 1181951–1181951. 8 indexed citations
6.
Wang, Yan, Kun Shi, Jiyuan Tu, et al.. (2023). Atractylenolide III Ameliorates Bile Duct Ligation-Induced Liver Fibrosis by Inhibiting the PI3K/AKT Pathway and Regulating Glutamine Metabolism. Molecules. 28(14). 5504–5504. 14 indexed citations
7.
Qu, Linghang, Kun Shi, Jing Xu, et al.. (2022). Atractylenolide-1 targets SPHK1 and B4GALT2 to regulate intestinal metabolism and flora composition to improve inflammation in mice with colitis. Phytomedicine. 98. 153945–153945. 48 indexed citations
8.
Xu, Jing, Chunlian Liu, Kun Shi, et al.. (2022). Atractyloside-A ameliorates spleen deficiency diarrhea by interfering with TLR4/MyD88/NF-κB signaling activation and regulating intestinal flora homeostasis. International Immunopharmacology. 107. 108679–108679. 27 indexed citations
9.
Shi, Kun, et al.. (2020). Multiple antiarrhythmic transplacental treatments for fetal supraventricular tachyarrhythmia. Medicine. 99(50). e23534–e23534. 2 indexed citations
10.
Liang, Shuang, et al.. (2020). Inhibition of RIPK1/RIPK3 ameliorates osteoclastogenesis through regulating NLRP3-dependent NF-κB and MAPKs signaling pathways. Biochemical and Biophysical Research Communications. 526(4). 1028–1035. 26 indexed citations
11.
Shi, Kun, et al.. (2018). A modified 6-form Tai Chi for patients with COPD. Complementary Therapies in Medicine. 39. 36–42. 27 indexed citations
12.
Huang, Hai‐Tsang, Joshiawa Paulk, Guang Yang, et al.. (2017). A Chemoproteomic Approach to Query the Degradable Kinome Using a Multi-kinase Degrader. Cell chemical biology. 25(1). 88–99.e6. 330 indexed citations breakdown →
13.
Shi, Kun, et al.. (2015). Analysis of the results of 838 cases of myocardial injury markers in neonates. Zhongguo jiceng yiyao. 22(11). 1632–1635. 1 indexed citations
14.
Shi, Kun, et al.. (2013). Prospects for circumventing aminoglycoside kinase mediated antibiotic resistance. Frontiers in Cellular and Infection Microbiology. 3. 22–22. 44 indexed citations
15.
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17.
Wong, Michael, et al.. (2008). Functional Divergence between Co-chaperones of Hsc70. Journal of Biological Chemistry. 283(40). 27100–27109. 63 indexed citations
18.
Shi, Kun, Satoshi Ugi, Kazuhiro Ikeda, et al.. (2007). Membrane localization of protein-tyrosine phosphatase 1B is essential for its activation of sterol regulatory element-binding protein-1 gene expression. Biochemical and Biophysical Research Communications. 363(3). 626–632. 13 indexed citations
19.
Shimizu, Shinya, Hiroshi Maegawa, Katsuya Egawa, et al.. (2002). Mechanism for Differential Effect of Protein-Tyrosine Phosphatase 1B on AktVersusMitogen-Activated Protein Kinase in 3T3-L1 Adipocytes. Endocrinology. 143(12). 4563–4569. 20 indexed citations
20.

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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