Yong Tang

5.5k total citations
204 papers, 4.1k citations indexed

About

Yong Tang is a scholar working on Physiology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Yong Tang has authored 204 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Physiology, 52 papers in Neurology and 45 papers in Cellular and Molecular Neuroscience. Recurrent topics in Yong Tang's work include Alzheimer's disease research and treatments (43 papers), Neuroinflammation and Neurodegeneration Mechanisms (40 papers) and Neurogenesis and neuroplasticity mechanisms (39 papers). Yong Tang is often cited by papers focused on Alzheimer's disease research and treatments (43 papers), Neuroinflammation and Neurodegeneration Mechanisms (40 papers) and Neurogenesis and neuroplasticity mechanisms (39 papers). Yong Tang collaborates with scholars based in China, United States and Singapore. Yong Tang's co-authors include Jens Randel Nyengaard, Bente Pakkenberg, Lisbeth Marner, Iván A. López, H. J. G. Gundersen, Feng‐lei Chao, Robert W. Baloh, Lin Jiang, Akira Ishiyama and Feng Ru Tang and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and The Journal of Comparative Neurology.

In The Last Decade

Yong Tang

197 papers receiving 4.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yong Tang China 33 1.0k 867 857 740 626 204 4.1k
Rudolf Kraftsik Switzerland 30 569 0.6× 1.4k 1.6× 697 0.8× 808 1.1× 679 1.1× 63 3.4k
Peter R. Mouton United States 36 1.0k 1.0× 1.4k 1.7× 1.1k 1.2× 1.3k 1.7× 1.2k 1.9× 100 5.3k
David T. Yew Hong Kong 43 772 0.8× 1.3k 1.5× 969 1.1× 1.8k 2.5× 422 0.7× 265 6.0k
Dara L. Dickstein United States 34 1.0k 1.0× 1.4k 1.6× 1.7k 2.0× 1.4k 1.9× 992 1.6× 59 5.0k
Benoı̂t Delatour France 32 623 0.6× 1.2k 1.4× 1.7k 1.9× 1.2k 1.6× 913 1.5× 72 3.8k
Caterina Motta Italy 33 1.4k 1.4× 555 0.6× 466 0.5× 516 0.7× 656 1.0× 86 3.4k
Irène Knuesel Switzerland 34 1.6k 1.5× 1.3k 1.5× 1.2k 1.4× 1.6k 2.1× 492 0.8× 60 5.7k
Wilma D. J. van de Berg Netherlands 39 897 0.9× 1.1k 1.3× 1.4k 1.6× 1.0k 1.4× 452 0.7× 130 4.5k
Alena Savonenko United States 33 679 0.7× 1.4k 1.6× 1.9k 2.2× 1.3k 1.7× 506 0.8× 74 4.4k
Christoph Laske Germany 31 660 0.6× 797 0.9× 1.3k 1.5× 604 0.8× 461 0.7× 94 3.3k

Countries citing papers authored by Yong Tang

Since Specialization
Citations

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

Fields of papers citing papers by Yong Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yong Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Yong Tang. A scholar is included among the top collaborators of Yong Tang 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 Yong Tang. Yong Tang 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.
Ren, Wenjing, Yafei Zhao, Xuan Li, et al.. (2025). Hippocampal P2X7 and A2A purinoceptors mediate cognitive impairment caused by long-lasting epileptic seizures. Theranostics. 15(7). 3159–3184. 4 indexed citations
2.
Zhou, Bin, Binjie Chen, Ruotian Jiang, et al.. (2025). Astrocyte Ezrin defines resilience to stress-induced depressive behaviours in mice. National Science Review. 13(2). nwaf480–nwaf480.
3.
Peng, Ye, Jiulin Tan, Chengmin Zhang, et al.. (2024). LL-37 and bisphosphonate co-delivery 3D-scaffold with antimicrobial and antiresorptive activities for bone regeneration. International Journal of Biological Macromolecules. 277(Pt 1). 134091–134091. 8 indexed citations
4.
Liu, Shan, Jing Tang, Xin Liang, et al.. (2024). Running exercise decreases microglial activation in the medial prefrontal cortex in an animal model of depression. Journal of Affective Disorders. 368. 674–685. 3 indexed citations
5.
Tang, Yong, et al.. (2024). Astrocytic adenosine A1 receptors: a new potential target for treating sepsis-associated encephalopathy. Purinergic Signalling. 21(3). 381–383. 1 indexed citations
6.
Zhang, Mengmeng, Xiangru Kong, Jing Chen, et al.. (2023). Dysfunction of GluN3A subunit is involved in depression-like behaviors through synaptic deficits. Journal of Affective Disorders. 332. 72–82. 2 indexed citations
7.
Liu, Mei, Lin Zhu, Yijing Guo, et al.. (2023). The effects of voluntary running exercise on the astrocytes of the medial prefrontal cortex in APP/PS1 mice. The Journal of Comparative Neurology. 531(11). 1147–1162. 3 indexed citations
8.
Jiang, Yuncheng, et al.. (2022). Parallel Core Maintenance of Dynamic Graphs. IEEE Transactions on Knowledge and Data Engineering. 35(9). 8919–8933. 3 indexed citations
9.
Zhao, Yafei, Alexei Verkhratsky, Yong Tang, & Péter Illés. (2022). Astrocytes and major depression: The purinergic avenue. Neuropharmacology. 220. 109252–109252. 49 indexed citations
10.
Liang, Xin, Jing Tang, Yanmin Luo, et al.. (2022). Exercise more efficiently regulates the maturation of newborn neurons and synaptic plasticity than fluoxetine in a CUS-induced depression mouse model. Experimental Neurology. 354. 114103–114103. 20 indexed citations
11.
Qin, Shukui, Jiafu Ji, Rui‐Hua Xu, et al.. (2021). Treatment Patterns and Outcomes in Chinese Patients with Gastric Cancer by HER2 Status: A Noninterventional Registry Study (EVIDENCE). The Oncologist. 26(9). e1567–e1580. 23 indexed citations
12.
Tang, Yong, Qi Wang, & Jie Liu. (2021). Microbiota-gut-brain axis: A novel potential target of ketogenic diet for epilepsy. Current Opinion in Pharmacology. 61. 36–41. 17 indexed citations
13.
Dong, Haisi, Guangqi Song, Danhui Ma, et al.. (2021). Improved Antiviral Activity of Classical Swine Fever Virus-Targeted siRNA by Tetrahedral Framework Nucleic Acid-Enhanced Delivery. ACS Applied Materials & Interfaces. 13(25). 29416–29423. 13 indexed citations
14.
15.
Lu, Sheng-Feng, et al.. (2012). [Considerations about study on mechanisms of thermal efficacies of moxibustion from activities of transient receptor potential family].. PubMed. 37(2). 151–4, 160. 3 indexed citations
16.
Shu, Yang, et al.. (2011). APPLICATION OF STEREOLOGICAL METHODS TO STUDY THE WHITE MATTER AND MYELINATED FIBERS THEREIN OF RAT BRAIN. Image Analysis & Stereology. 27(2). 125–125. 10 indexed citations
17.
Ma, Louyan, Dongmin Zhang, Yong Tang, et al.. (2011). Ghrelin-Attenuated Cognitive Dysfunction in Streptozotocin-induced Diabetic Rats. Alzheimer Disease & Associated Disorders. 25(4). 352–363. 36 indexed citations
18.
Shu, Yang, et al.. (2008). Sex differences in the white matter and myelinated nerve fibers of Long-Evans rats. Brain Research. 1216. 16–23. 32 indexed citations
19.
Li, Chen, et al.. (2008). Unbiased stereological quantification of unmyelinated fibers in the rat brain white matter. Neuroscience Letters. 437(1). 38–41. 5 indexed citations
20.
Marner, Lisbeth, Jens Randel Nyengaard, Yong Tang, & Bente Pakkenberg. (2003). Marked loss of myelinated nerve fibers in the human brain with age. The Journal of Comparative Neurology. 462(2). 144–152. 440 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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