Dong‐Ya Zhu

6.4k total citations · 2 hit papers
90 papers, 4.8k citations indexed

About

Dong‐Ya Zhu is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Neurology. According to data from OpenAlex, Dong‐Ya Zhu has authored 90 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Cellular and Molecular Neuroscience, 33 papers in Molecular Biology and 30 papers in Neurology. Recurrent topics in Dong‐Ya Zhu's work include Neuroscience and Neuropharmacology Research (31 papers), Neuroinflammation and Neurodegeneration Mechanisms (26 papers) and Neurogenesis and neuroplasticity mechanisms (17 papers). Dong‐Ya Zhu is often cited by papers focused on Neuroscience and Neuropharmacology Research (31 papers), Neuroinflammation and Neurodegeneration Mechanisms (26 papers) and Neurogenesis and neuroplasticity mechanisms (17 papers). Dong‐Ya Zhu collaborates with scholars based in China, United States and Canada. Dong‐Ya Zhu's co-authors include Chun‐Xia Luo, Li Zhou, Hai‐Yin Wu, Li‐Juan Zhu, Xian‐Hui Zhu, Qi‐Gang Zhou, Xu Chu, Qi‐Gang Zhou, Chunyu Yin and Mengying Liu and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Dong‐Ya Zhu

86 papers receiving 4.8k citations

Hit Papers

Sucrose preference test for measurement ... 2009 2026 2014 2020 2018 2009 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dong‐Ya Zhu China 36 1.7k 1.5k 1.1k 946 761 90 4.8k
Chun‐Xia Luo China 29 958 0.6× 1.0k 0.7× 691 0.6× 717 0.8× 665 0.9× 64 3.4k
Tadahiro Numakawa Japan 41 1.9k 1.1× 2.1k 1.4× 742 0.7× 501 0.5× 984 1.3× 87 5.3k
Carlos Alexandre Netto Brazil 50 1.7k 1.0× 1.9k 1.3× 1.4k 1.3× 1.4k 1.5× 711 0.9× 257 7.5k
Władysław Lasoń Poland 43 2.3k 1.4× 2.7k 1.8× 1.1k 1.0× 679 0.7× 1.3k 1.7× 278 6.9k
Piyarat Govitrapong Thailand 43 1.8k 1.1× 1.5k 1.0× 1.4k 1.3× 656 0.7× 326 0.4× 230 6.2k
Kazuhiro Takuma Japan 45 2.7k 1.6× 2.8k 1.8× 1.1k 1.0× 877 0.9× 769 1.0× 159 6.7k
Hongxin Dong United States 35 956 0.6× 916 0.6× 1.5k 1.4× 535 0.6× 730 1.0× 91 4.0k
Bogusława Budziszewska Poland 38 1.2k 0.7× 1.3k 0.8× 529 0.5× 494 0.5× 1.3k 1.7× 197 4.8k
Thomas C. Foster United States 47 1.8k 1.1× 2.7k 1.7× 1.4k 1.3× 1.6k 1.7× 786 1.0× 109 6.4k
Hiroshi Katsuki Japan 48 3.0k 1.8× 2.4k 1.5× 1.1k 1.0× 1.3k 1.4× 553 0.7× 248 7.9k

Countries citing papers authored by Dong‐Ya Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Dong‐Ya Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong‐Ya Zhu. 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 Dong‐Ya Zhu. The network helps show where Dong‐Ya Zhu may publish in the future.

Co-authorship network of co-authors of Dong‐Ya Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Dong‐Ya Zhu. A scholar is included among the top collaborators of Dong‐Ya Zhu 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 Dong‐Ya Zhu. Dong‐Ya Zhu 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.
Liu, Quanyou, et al.. (2025). Diamondoids evolution in various phase states of ultra-deep hydrocarbons in Tarim Basin, NW China. Petroleum Science. 22(4). 1446–1464.
2.
3.
Lin, Yu‐Hui, Na Li, Wei Chen, et al.. (2025). Nos1+ neurons are critical for motor learning and post-stroke motor recovery. Cell Reports. 44(10). 116322–116322. 1 indexed citations
4.
Zhu, Li‐Juan, Fei Li, & Dong‐Ya Zhu. (2023). nNOS and Neurological, Neuropsychiatric Disorders: A 20-Year Story. Neuroscience Bulletin. 39(9). 1439–1453. 24 indexed citations
5.
Yang, Di, Yu‐Hui Lin, Hai‐Yin Wu, et al.. (2023). Cerebral organoids transplantation repairs infarcted cortex and restores impaired function after stroke. npj Regenerative Medicine. 8(1). 27–27. 46 indexed citations
6.
Sun, Nan, Yajuan Qin, Xu Chu, et al.. (2022). Design of fast-onset antidepressant by dissociating SERT from nNOS in the DRN. Science. 378(6618). 390–398. 64 indexed citations
7.
Hong, Yuan, Mengdan Tao, Luping Shen, et al.. (2022). Depressive patient‐derived GABA interneurons reveal abnormal neural activity associated with HTR2C. EMBO Molecular Medicine. 15(1). e16364–e16364. 37 indexed citations
8.
Zeng, Jiaqi, Ping Su, Haiying Liang, et al.. (2022). An Injectable Hydrogel for Treatment of Chronic Neuropathic Pain. Macromolecular Bioscience. 22(6). e2100529–e2100529. 6 indexed citations
9.
Yin, Chunyu, Shuying Huang, Ling Gao, et al.. (2021). Neuronal Nitric Oxide Synthase in Nucleus Accumbens Specifically Mediates Susceptibility to Social Defeat Stress through Cyclin-Dependent Kinase 5. Journal of Neuroscience. 41(11). 2523–2539. 16 indexed citations
10.
Liang, Haiying, Zhijin Chen, Hui Xiao, et al.. (2020). nNOS-expressing neurons in the vmPFC transform pPVT-derived chronic pain signals into anxiety behaviors. Nature Communications. 11(1). 2501–2501. 55 indexed citations
11.
Qin, Cheng‐Feng, Hai‐Yin Wu, Cheng-Yun Cai, et al.. (2020). Dorsal Hippocampus to Infralimbic Cortex Circuit is Essential for the Recall of Extinction Memory. Cerebral Cortex. 31(3). 1707–1718. 21 indexed citations
12.
Qin, Cheng‐Feng, Cheng-Yun Cai, Chen Chen, et al.. (2019). Uncoupling nNOS-PSD-95 in the ACC can inhibit contextual fear generalization. Biochemical and Biophysical Research Communications. 513(1). 248–254. 8 indexed citations
13.
Qin, Cheng‐Feng, Cheng-Yun Cai, Ying Zhou, et al.. (2019). Anterior Cingulate Cortex to Ventral Hippocampus Circuit Mediates Contextual Fear Generalization. Journal of Neuroscience. 39(29). 5728–5739. 81 indexed citations
14.
Zhang, Yu, Zhu Zhu, Haiying Liang, et al.. (2018). nNOSCAPON interaction mediates amyloid‐β‐induced neurotoxicity, especially in the early stages. Aging Cell. 17(3). e12754–e12754. 28 indexed citations
15.
Zhou, Qi‐Gang, Xian‐Hui Zhu, Ashley D. Nemes, & Dong‐Ya Zhu. (2018). Neuronal nitric oxide synthase and affective disorders. IBRO Reports. 5. 116–132. 74 indexed citations
16.
Zhang, Fengyun, Cheng‐Feng Qin, Yu‐Hui Lin, et al.. (2016). Phosphofructokinase-1 Negatively Regulates Neurogenesis from Neural Stem Cells. Neuroscience Bulletin. 32(3). 205–216. 16 indexed citations
17.
Zhou, Han, Liyan Gao, Yu‐Hui Lin, et al.. (2016). Neuroprotection of taurine against reactive oxygen species is associated with inhibiting NADPH oxidases. European Journal of Pharmacology. 777. 129–135. 38 indexed citations
18.
Zhu, Li‐Juan, Tingyou Li, Chun‐Xia Luo, et al.. (2014). CAPON-nNOS coupling can serve as a target for developing new anxiolytics. Nature Medicine. 20(9). 1050–1054. 79 indexed citations
19.
Meng, Zhuo‐Xian, Jia Nie, Ling Jing, et al.. (2008). Activation of liver X receptors inhibits pancreatic islet beta cell proliferation through cell cycle arrest. Diabetologia. 52(1). 125–135. 62 indexed citations
20.
Xu, Jin, Zheng Zhu, Jie Wu, et al.. (2007). Immunization with a recombinant GnRH vaccine conjugated to heat shock protein 65 inhibits tumor growth in orthotopic prostate cancer mouse model. Cancer Letters. 259(2). 240–250. 16 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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