Yun Gu

5.3k total citations · 1 hit paper
82 papers, 4.1k citations indexed

About

Yun Gu is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Biomaterials. According to data from OpenAlex, Yun Gu has authored 82 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Cellular and Molecular Neuroscience, 40 papers in Molecular Biology and 14 papers in Biomaterials. Recurrent topics in Yun Gu's work include Nerve injury and regeneration (34 papers), Neurogenesis and neuroplasticity mechanisms (13 papers) and Electrospun Nanofibers in Biomedical Applications (9 papers). Yun Gu is often cited by papers focused on Nerve injury and regeneration (34 papers), Neurogenesis and neuroplasticity mechanisms (13 papers) and Electrospun Nanofibers in Biomedical Applications (9 papers). Yun Gu collaborates with scholars based in China, United States and Australia. Yun Gu's co-authors include David O. Morgan, Xiaosong Gu, Jody Rosenblatt, Fei Ding, Michael Su, Yumin Yang, Charles A. Dinarello, Adrian Puren, Giamila Fantuzzi and Jin Pei and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Yun Gu

80 papers receiving 4.0k citations

Hit Papers

Cell cycle regulation of CDK2 activity by phosphorylation... 1992 2026 2003 2014 1992 100 200 300 400 500
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. Cell cycle regulation of CDK2 activity by phosphorylation of Thr160 and Tyr15.
    1992 557 citations Yun Gu et al. profile →

Peers

Yun Gu
Paul G. Genever United Kingdom
Rona S. Carroll United States
Fang Mei United States
Seyed Javad Mowla Iran
Chun-Chi Liang United States
George Dickson United Kingdom
Tomo Šarić Germany
Maarja Andaloussi Mäe Sweden
Li Sun China
Oren Levy United States
Paul G. Genever United Kingdom
Yun Gu
Citations per year, relative to Yun Gu Yun Gu (= 1×) peers Paul G. Genever

Countries citing papers authored by Yun Gu

Since Specialization
Citations

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

Fields of papers citing papers by Yun Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yun Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Yun Gu. A scholar is included among the top collaborators of Yun Gu 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 Yun Gu. Yun Gu 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.
Gu, Yun, et al.. (2025). Enhancing whole slide image classification through label denoising in a multi-instance learning framework. Biomedical Signal Processing and Control. 105. 107599–107599.
2.
Liu, Tianqing, Guicai Li, Bi‐Qin Lai, et al.. (2023). Role of inflammation in neurological damage and regeneration following spinal cord injury and its therapeutic implications. Burns & Trauma. 11. tkac054–tkac054. 33 indexed citations
3.
Gong, Leilei, Yun Gu, Xinghui Wang, et al.. (2023). SnRNA-seq reveals the heterogeneity of spinal ventral horn and mechanism of motor neuron axon regeneration. iScience. 26(8). 107264–107264. 3 indexed citations
4.
5.
Gong, Leilei, Yun Gu, Xiaoxiao Han, et al.. (2022). Spatiotemporal Dynamics of the Molecular Expression Pattern and Intercellular Interactions in the Glial Scar Response to Spinal Cord Injury. Neuroscience Bulletin. 39(2). 213–244. 60 indexed citations
6.
Zhu, Changlai, Bin Zhang, Jinghui Xu, et al.. (2021). BMSC-derived extracellular matrix better optimizes the microenvironment to support nerve regeneration. Biomaterials. 280. 121251–121251. 59 indexed citations
7.
Wang, Zilong, Chen Ouyang, Yun Gu, et al.. (2020). Central opioid receptors mediate morphine-induced itch and chronic itch via disinhibition. Brain. 144(2). 665–681. 60 indexed citations
8.
Du, Wenting, et al.. (2019). Risk factors for venous thromboembolism in individuals undergoing coronary artery bypass grafting. Journal of Vascular Surgery Venous and Lymphatic Disorders. 8(4). 551–557. 2 indexed citations
9.
Xue, Chengbin, Hui Zhu, Xiaosong Gu, et al.. (2017). Bone marrow mesenchymal stem cell-derived acellular matrix-coated chitosan/silk scaffolds for neural tissue regeneration. Journal of Materials Chemistry B. 5(6). 1246–1257. 38 indexed citations
10.
Xue, Chengbin, Hui Zhu, Xiaosong Gu, et al.. (2017). Electrospun silk fibroin‐based neural scaffold for bridging a long sciatic nerve gap in dogs. Journal of Tissue Engineering and Regenerative Medicine. 12(2). e1143–e1153. 76 indexed citations
11.
Gu, Yun, Chu Chen, Sheng Yi, et al.. (2015). miR-sc8 Inhibits Schwann Cell Proliferation and Migration by Targeting Egfr. PLoS ONE. 10(12). e0145185–e0145185. 26 indexed citations
12.
Gu, Yun, Jian Yang, Jing Li, et al.. (2015). Different Astrocytic Activation between Adult Gekko japonicus and Rats during Wound Healing In Vitro. PLoS ONE. 10(5). e0127663–e0127663. 13 indexed citations
13.
Li, Shiying, Xinghui Wang, Yun Gu, et al.. (2014). Let-7 microRNAs Regenerate Peripheral Nerve Regeneration by Targeting Nerve Growth Factor. Molecular Therapy. 23(3). 423–433. 115 indexed citations
14.
Gu, Yun, et al.. (2013). Molecular cloning of tubulin beta 3 (<I>TUBB3</I>) in <I>Gekko japonicus</I> and preparation of its polyclonal antibody. Zoological Research. 33(4). 395–401. 1 indexed citations
15.
Yang, Yumin, Fei Ding, Dengbing Yao, et al.. (2011). Repair of Rat Sciatic Nerve Gap by a Silk Fibroin-Based Scaffold Added with Bone Marrow Mesenchymal Stem Cells. Tissue Engineering Part A. 17(17-18). 2231–2244. 87 indexed citations
16.
Wang, Jie, Fei Ding, Yun Gu, Jie Liu, & Xiaosong Gu. (2009). Bone marrow mesenchymal stem cells promote cell proliferation and neurotrophic function of Schwann cells in vitro and in vivo. Brain Research. 1262. 7–15. 105 indexed citations
17.
Liu, Mei, et al.. (2009). Establishment and characterization of two cell lines derived from primary cultures of Gekko japonicus cerebral cortex. Cell Biology International. 34(2). 153–161. 8 indexed citations
18.
Liu, Mei, Xiaosong Gu, Qi Zhang, et al.. (2006). Tpc1808 Increases Expression of NF-H in PC12 Cells. Journal of Molecular Neuroscience. 29(2). 123–130. 2 indexed citations
19.
Gu, Yun. (2000). Effects and Binding Sites of Glycyrrhetinic Acid and Glycyrrhizin on Isolated Rat Hepatocyte Membrane. 1 indexed citations
20.
Puren, Adrian, Giamila Fantuzzi, Yun Gu, Michael Su, & Charles A. Dinarello. (1998). Interleukin-18 (IFNgamma-inducing factor) induces IL-8 and IL-1beta via TNFalpha production from non-CD14+ human blood mononuclear cells.. Journal of Clinical Investigation. 101(3). 711–721. 486 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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