Shuyan Li

1.2k total citations · 1 hit paper
53 papers, 879 citations indexed

About

Shuyan Li is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Shuyan Li has authored 53 papers receiving a total of 879 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 13 papers in Oncology and 11 papers in Cancer Research. Recurrent topics in Shuyan Li's work include Cancer-related Molecular Pathways (10 papers), DNA Repair Mechanisms (9 papers) and RNA modifications and cancer (9 papers). Shuyan Li is often cited by papers focused on Cancer-related Molecular Pathways (10 papers), DNA Repair Mechanisms (9 papers) and RNA modifications and cancer (9 papers). Shuyan Li collaborates with scholars based in China, Australia and United States. Shuyan Li's co-authors include Ju‐Hua Ni, Hong‐Ti Jia, Guo‐Shun An, Xiaoyu Wang, Jiaqi Meng, Shihao Wang, Yuan Tang, Liping Xing, Wenzheng Wu and Yufan Chen and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Free Radical Biology and Medicine and International Journal of Molecular Sciences.

In The Last Decade

Shuyan Li

51 papers receiving 870 citations

Hit Papers

Mechanisms of circRNA/lnc... 2023 2026 2024 2023 40 80 120
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. Mechanisms of circRNA/lncRNA-miRNA interactions and applications in disease and drug research
    2023 120 citations Shuyan Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuyan Li China 17 600 240 130 114 81 53 879
Changjing Wu China 17 556 0.9× 178 0.7× 90 0.7× 66 0.6× 42 0.5× 41 1.1k
Jin Meng China 19 721 1.2× 347 1.4× 129 1.0× 211 1.9× 39 0.5× 42 1.0k
Yongmei Li China 18 713 1.2× 384 1.6× 120 0.9× 40 0.4× 74 0.9× 45 986
Jieun Seo South Korea 17 373 0.6× 172 0.7× 71 0.5× 88 0.8× 66 0.8× 42 741
Viviane Aline Oliveira Silva Brazil 16 504 0.8× 202 0.8× 103 0.8× 72 0.6× 78 1.0× 52 819
Jason Kang South Korea 14 679 1.1× 188 0.8× 146 1.1× 197 1.7× 145 1.8× 22 1.0k
Zhijie Liu United States 18 878 1.5× 195 0.8× 138 1.1× 185 1.6× 162 2.0× 46 1.4k
А. Ф. Садритдинова Russia 18 564 0.9× 205 0.9× 88 0.7× 233 2.0× 40 0.5× 32 1.0k

Countries citing papers authored by Shuyan Li

Since Specialization
Citations

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

Fields of papers citing papers by Shuyan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuyan Li

This figure shows the co-authorship network connecting the top 25 collaborators of Shuyan Li. A scholar is included among the top collaborators of Shuyan Li 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 Shuyan Li. Shuyan Li 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.
Song, Qiaoying, et al.. (2025). Trichosanthes kirilowii Maxim. Polysaccharide attenuates diabetes through the synergistic impact of lipid metabolism and modulating gut microbiota. Current Research in Food Science. 10. 100977–100977. 4 indexed citations
2.
Cao, Chunxiang, Lingfang Zhuang, Peizhan Chen, et al.. (2024). Elucidating the changes in the heterogeneity and function of radiation-induced cardiac macrophages using single-cell RNA sequencing. Frontiers in Immunology. 15. 1363278–1363278. 3 indexed citations
3.
Li, Shuyan, et al.. (2024). Histone deacetylase 6 controls cardiac fibrosis and remodelling through the modulation of TGF‐β1/Smad2/3 signalling in post‐infarction mice. Journal of Cellular and Molecular Medicine. 28(17). e70063–e70063. 9 indexed citations
4.
5.
Cao, Jiashun, Qiu Li, Lifan Zhang, et al.. (2023). ZFP36 loss-mediated BARX1 stabilization promotes malignant phenotypes by transactivating master oncogenes in NSCLC. Cell Death and Disease. 14(8). 527–527. 9 indexed citations
6.
Li, Shuyan, Shiheng Lu, Lei Wang, et al.. (2023). Effects of amygdalin on ferroptosis and oxidative stress in diabetic retinopathy progression via the NRF2/ARE signaling pathway. Experimental Eye Research. 234. 109569–109569. 27 indexed citations
7.
Li, Shuyan, Shiheng Lu, Lei Zhang, et al.. (2021). Basic regulatory effects and clinical value of metalloproteinase-14 and extracellular matrix metalloproteinase inducer in diabetic retinopathy. Materials Express. 11(6). 873–879. 2 indexed citations
8.
Gui, Songtao, Linfeng Yang, Jianbo Li, et al.. (2020). ZEAMAP, a Comprehensive Database Adapted to the Maize Multi-Omics Era. iScience. 23(6). 101241–101241. 64 indexed citations
9.
Yang, Shengyong, Yi Li, Guo‐Shun An, et al.. (2018). DNA Damage-Response Pathway Heterogeneity of Human Lung Cancer A549 and H1299 Cells Determines Sensitivity to 8-Chloro-Adenosine. International Journal of Molecular Sciences. 19(6). 1587–1587. 14 indexed citations
10.
Li, Shuyan, Yan Sun, Yan Shi, et al.. (2014). Protective effect and mechanism of glutaredoxin 1 on coronary arteries endothelial cells damage induced by high glucose. Bio-Medical Materials and Engineering. 24(6). 3897–3903. 14 indexed citations
11.
Liu, Ling, Guo‐Shun An, Shuyan Li, et al.. (2014). E2F1 regulates p53R2 gene expression in p53-deficient cells. Molecular and Cellular Biochemistry. 399(1-2). 179–188. 11 indexed citations
12.
Li, Shuyan. (2013). The Oncogenic and Tumor Suppressor Activities of ATF-2. 1 indexed citations
13.
Han, Yuying, Zhe Zhou, Yaqiong Jin, et al.. (2013). E2F1-mediated DNA damage is implicated in 8-Cl-adenosine-induced chromosome missegregation and apoptosis in human lung cancer H1299 cells. Molecular and Cellular Biochemistry. 384(1-2). 187–196. 3 indexed citations
14.
Duan, Hongying, Guosheng Wu, Shuyan Li, et al.. (2012). E2F1 enhances 8-Chloro-adenosine-induced G2/M arrest and apoptosis in A549 and H1299 lung cancer cells. Biochemistry (Moscow). 77(3). 261–269. 4 indexed citations
15.
16.
Du, Chao, Yaqiong Jin, Shuyan Li, et al.. (2012). Effects of Myogenin on Expression of Late Muscle Genes through MyoD-Dependent Chromatin Remodeling Ability of Myogenin. Molecules and Cells. 34(2). 133–142. 20 indexed citations
17.
Zhang, Liqiu, Xingli Dong, Hengyu Zhao, et al.. (2012). Apoptin selectively induces the apoptosis of tumor cells by suppressing the transcription of HSP70. Tumor Biology. 34(1). 577–585. 20 indexed citations
18.
Li, Shuyan. (2011). The clinical study of nonspecific low back pain with neuromuscular activation technology.
19.
20.
Zhang, Hongyu, Yanyan Gu, Lan Yuan, et al.. (2004). Exposure of Human Lung Cancer Cells to 8-Chloro-Adenosine Induces G2/M Arrest and Mitotic Catastrophe. Neoplasia. 6(6). 802–812. 33 indexed citations

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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