Kunshan Zhang

1.8k total citations · 1 hit paper
26 papers, 655 citations indexed

About

Kunshan Zhang is a scholar working on Molecular Biology, Cancer Research and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kunshan Zhang has authored 26 papers receiving a total of 655 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Cancer Research and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kunshan Zhang's work include MicroRNA in disease regulation (6 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers) and CRISPR and Genetic Engineering (3 papers). Kunshan Zhang is often cited by papers focused on MicroRNA in disease regulation (6 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers) and CRISPR and Genetic Engineering (3 papers). Kunshan Zhang collaborates with scholars based in China, United States and Italy. Kunshan Zhang's co-authors include Siguang Li, Yuping Luo, Liqiang Zhou, Yi Sun, Jiping Liu, Changhong Zheng, Yi Eve Sun, Yufang Shi, Weihong Ge and Chen Li and has published in prestigious journals such as PLoS ONE, Biochemical and Biophysical Research Communications and Frontiers in Immunology.

In The Last Decade

Kunshan Zhang

26 papers receiving 654 citations

Hit Papers

Temporal and spatial cellular and molecular pathological ... 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kunshan Zhang China 14 368 139 120 103 90 26 655
Cristina Porcheri Switzerland 12 289 0.8× 87 0.6× 62 0.5× 96 0.9× 140 1.6× 17 742
Yaobing Yao China 13 457 1.2× 218 1.6× 157 1.3× 246 2.4× 89 1.0× 28 751
Anne DeChant United States 8 292 0.8× 69 0.5× 242 2.0× 75 0.7× 82 0.9× 10 779
Candice Chapouly France 14 344 0.9× 60 0.4× 59 0.5× 49 0.5× 275 3.1× 29 749
Jung-Yu C. Hsu United States 10 242 0.7× 132 0.9× 115 1.0× 197 1.9× 105 1.2× 11 662
Sandrine Bichet Switzerland 10 323 0.9× 93 0.7× 100 0.8× 22 0.2× 42 0.5× 14 862
Jessica Foraker United States 9 292 0.8× 56 0.4× 292 2.4× 43 0.4× 117 1.3× 9 787
R Liu United States 8 304 0.8× 36 0.3× 130 1.1× 101 1.0× 39 0.4× 9 898
Raquel Cuevas‐Díaz Durán Mexico 12 273 0.7× 174 1.3× 49 0.4× 42 0.4× 79 0.9× 21 447
Danyang He China 11 344 0.9× 140 1.0× 48 0.4× 39 0.4× 193 2.1× 16 751

Countries citing papers authored by Kunshan Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Kunshan Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunshan Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Kunshan Zhang. A scholar is included among the top collaborators of Kunshan Zhang 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 Kunshan Zhang. Kunshan Zhang 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.
Chen, Fei, Kunshan Zhang, Minjun Wang, et al.. (2024). VEGF‐FGF Signaling Activates Quiescent CD63+ Liver Stem Cells to Proliferate and Differentiate (Adv. Sci. 33/2024). Advanced Science. 11(33). 6 indexed citations
2.
Zhao, Weijia, Yujia Wang, Xinwei Zhang, et al.. (2023). Impaired thymic iNKT cell differentiation at early precursor stage in murine haploidentical bone marrow transplantation with GvHD. Frontiers in Immunology. 14. 1203614–1203614. 1 indexed citations
3.
Li, Chen, Zhourui Wu, Liqiang Zhou, et al.. (2022). Temporal and spatial cellular and molecular pathological alterations with single-cell resolution in the adult spinal cord after injury. Signal Transduction and Targeted Therapy. 7(1). 65–65. 148 indexed citations breakdown →
4.
Zhang, Kunshan, Lixi Li, Yong Hu, et al.. (2022). Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulated in Exercise in a Mouse Model of Parkinson’s Disease. Frontiers in Aging Neuroscience. 14. 891644–891644. 7 indexed citations
5.
Zhang, Chunxue, Liqiang Zhou, Zhen Wang, et al.. (2021). Eradication of specific donor-dependent variations of mesenchymal stem cells in immunomodulation to enhance therapeutic values. Cell Death and Disease. 12(4). 357–357. 39 indexed citations
6.
Chen, Ling, Cuiping Yang, Ning‐Ning Song, et al.. (2021). Pten is a key intrinsic factor regulating raphe 5-HT neuronal plasticity and depressive behaviors in mice. Translational Psychiatry. 11(1). 186–186. 11 indexed citations
8.
Wang, Yujia, Yang Liu, Qiang Shi, et al.. (2020). Transcriptional heterogeneity of clonal plasma cells and immune evasion in immunoglobulin light chain amyloidosis. International Journal of Hematology. 113(2). 231–242. 2 indexed citations
9.
Hu, Yong, Kunshan Zhang, Tianyu Zhang, et al.. (2020). Exercise Reverses Dysregulation of T-Cell-Related Function in Blood Leukocytes of Patients With Parkinson's Disease. Frontiers in Neurology. 10. 1389–1389. 8 indexed citations
10.
Zhang, Peng, Jian He, Fei Wang, et al.. (2019). Hemojuvelin is a novel suppressor for Duchenne muscular dystrophy and age‐related muscle wasting. Journal of Cachexia Sarcopenia and Muscle. 10(3). 557–573. 17 indexed citations
11.
Li, Mingyang, Weijia Zhao, Yifan Wang, et al.. (2019). A wave of Foxp3+ regulatory T cell accumulation in the neonatal liver plays unique roles in maintaining self-tolerance. Cellular and Molecular Immunology. 17(5). 507–518. 26 indexed citations
12.
Huang, Yin, Qing Li, Kunshan Zhang, et al.. (2019). Single cell transcriptomic analysis of human mesenchymal stem cells reveals limited heterogeneity. Cell Death and Disease. 10(5). 368–368. 77 indexed citations
13.
Liu, Jiping, Huina Zhang, Liqiang Zhou, et al.. (2017). Single-cell transcriptomics reveals gene signatures and alterations associated with aging in distinct neural stem/progenitor cell subpopulations. Protein & Cell. 9(4). 351–364. 44 indexed citations
15.
Chen, Xiaoying, Kunshan Zhang, Liqiang Zhou, et al.. (2016). Coupled electrophysiological recording and single cell transcriptome analyses revealed molecular mechanisms underlying neuronal maturation. Protein & Cell. 7(3). 175–186. 36 indexed citations
16.
Zhou, Jing, Chencheng Wang, Kunshan Zhang, et al.. (2016). Generation of Human Embryonic Stem Cell Line Expressing zsGreen in Cholinergic Neurons Using CRISPR/Cas9 System. Neurochemical Research. 41(8). 2065–2074. 10 indexed citations
18.
Luo, Yuping, Chun Li, Xi Gong, et al.. (2013). Splicing-Related Features of Introns Serve to Propel Evolution. PLoS ONE. 8(3). e58547–e58547. 4 indexed citations
19.
Gong, Xi, Kunshan Zhang, Junbang Wang, et al.. (2013). MicroRNA-130b targets Fmr1 and regulates embryonic neural progenitor cell proliferation and differentiation. Biochemical and Biophysical Research Communications. 439(4). 493–500. 26 indexed citations
20.
Hu, Ganlu, Kevin Huang, Juehua Yu, et al.. (2012). Identification of miRNA Signatures during the Differentiation of hESCs into Retinal Pigment Epithelial Cells. PLoS ONE. 7(7). e37224–e37224. 28 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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