Feng Yue

1.5k total citations · 1 hit paper
78 papers, 1.1k citations indexed

About

Feng Yue is a scholar working on Physiology, Cellular and Molecular Neuroscience and Neurology. According to data from OpenAlex, Feng Yue has authored 78 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Physiology, 19 papers in Cellular and Molecular Neuroscience and 19 papers in Neurology. Recurrent topics in Feng Yue's work include Parkinson's Disease Mechanisms and Treatments (13 papers), Alzheimer's disease research and treatments (11 papers) and Neuroscience and Neural Engineering (8 papers). Feng Yue is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (13 papers), Alzheimer's disease research and treatments (11 papers) and Neuroscience and Neural Engineering (8 papers). Feng Yue collaborates with scholars based in China, United States and United Kingdom. Feng Yue's co-authors include Piu Chan, Piu Chan, Haonan Li, Zhongwei Gu, Zhiqian Li, Qiyong Gong, Huatian Gan, Qiang Luo, Kui Luo and Xue Li and has published in prestigious journals such as Nature Communications, Scientific Reports and Biological Psychiatry.

In The Last Decade

Feng Yue

69 papers receiving 1.1k citations

Hit Papers

align trajectories

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.

Stimuli-activatable nanomedicine meets cancer theranostics

2023 154 citations Haonan Li, Feng Yue et al. Theranostics profile →

Peers

Feng Yue

MB

CMN

NEURO

PHYSI

NEURO

Yilin Tang China

Neil U. Barua United Kingdom

Michael Erkkinen United States

Naoto Sakai Japan

Johanna Öberg Sweden

Parviz Shahabi Iran

Ranjana Patnaik India

Clinton Turner New Zealand

Xinhui Li China

Yilin Tang China

Feng Yue

272 ×1.0

MB

186 ×0.7

CMN

407 ×1.8

NEURO

157 ×0.9

PHYSI

94 ×0.8

NEURO

Citations per year, relative to Feng Yue Feng Yue (= 1×) peers Yilin Tang

Countries citing papers authored by Feng Yue

Since Specialization

Citations

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

Fields of papers citing papers by Feng Yue

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Yue

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Yue. A scholar is included among the top collaborators of Feng Yue 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 Feng Yue. Feng Yue is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Li, Jifeng, et al.. (2025). A Cross-Crop and Cross-Regional Generalized Deep Learning Framework for Intelligent Disease Detection and Economic Decision Support in Horticulture. Horticulturae. 11(11). 1397–1397.

2.

Zhang, Wenchang, Ping Chen, Siyao Li, et al.. (2025). Amyloid-β oligomers drive amyloid deposit and cascaded tau pathology of Alzheimer's disease in aged brains of non-human primates. Journal of genetics and genomics. 52(11). 1367–1375. 4 indexed citations

3.

Wang, Honglei, Tao Xu, Ziqi Wang, et al.. (2025). Comparable perioperative performance between three robotic system for robot-assisted partial nephrectomy to treat early renal cancer. Scientific Reports. 15(1). 31402–31402.

4.

Yang, Qunhui, et al.. (2024). Integrative analysis of gut microbiota and fecal metabolites in cynomolgus monkeys with spontaneous type 2 diabetes mellitus. Microbial Pathogenesis. 199. 107228–107228. 5 indexed citations

5.

Guan, Xin‐Yuan, et al.. (2024). Analysis of eplerenone in the FDA adverse event reporting system (FAERS) database: a focus on overall patient population and gender-specific subgroups. Frontiers in Pharmacology. 15. 1417951–1417951. 2 indexed citations

6.

Wang, Xinran, et al.. (2024). Exenatide-Modified Deferoxamine-Based Nanoparticles Ameliorates Neurological Deficits in Parkinson’s Disease Mice. International Journal of Nanomedicine. Volume 19. 10401–10414. 8 indexed citations

7.

Tang, Lei, Mengyao Huang, Yi Wei, et al.. (2023). A primate nigrostriatal atlas of neuronal vulnerability and resilience in a model of Parkinson’s disease. Nature Communications. 14(1). 7497–7497. 13 indexed citations

8.

Yue, Feng, et al.. (2023). Combined untargeted and targeted lipidomics approaches reveal potential biomarkers in type 2 diabetes mellitus cynomolgus monkeys. Journal of Medical Primatology. 53(1). e12688–e12688. 2 indexed citations

9.

Li, Haonan, Feng Yue, Qiang Luo, et al.. (2023). Stimuli-activatable nanomedicine meets cancer theranostics. Theranostics. 13(15). 5386–5417. 154 indexed citations breakdown →

10.

Coelho, Diego R., Flávio R. Palma, Verônica Paviani, et al.. (2023). SOCS1 regulates a subset of NFκB-target genes through direct chromatin binding and defines macrophage functional phenotypes. iScience. 26(4). 106442–106442. 7 indexed citations

11.

Gao, Hui, et al.. (2020). Effect of FAT1 gene expression on the prognosis of medulloblastoma in children. Medicine. 99(46). e23020–e23020. 1 indexed citations

12.

Yan, Ru, et al.. (2019). Effect of clemastine fumarate on TLR4/PI3K/Akt signaling pathway during hypoxia-reoxygenation in rat cardiomyocytes. Zhonghua mazuixue zazhi. 39(5). 610–612. 1 indexed citations

13.

Ren, Guoping, Jiaqing Yan, Donghong Li, et al.. (2017). Rapid focal cooling attenuates cortical seizures in a primate epilepsy model. Experimental Neurology. 295. 202–210. 7 indexed citations

14.

Li, Zhihui, Xingjun Chen, Tao Wang, et al.. (2017). The Corticostriatal Adenosine A2A Receptor Controls Maintenance and Retrieval of Spatial Working Memory. Biological Psychiatry. 83(6). 530–541. 40 indexed citations

15.

Yue, Feng, et al.. (2016). Age- and sex-related changes in fasting plasma glucose and lipoprotein in cynomolgus monkeys. Lipids in Health and Disease. 15(1). 111–111. 14 indexed citations

16.

Zhang, Song, Yilin Song, Mixia Wang, et al.. (2016). A silicon based implantable microelectrode array for electrophysiological and dopamine recording from cortex to striatum in the non-human primate brain. Biosensors and Bioelectronics. 85. 53–61. 50 indexed citations

17.

Yang, Libo, et al.. (2015). Metabolic syndrome and the risk of bone fractures: A Meta-analysis of prospective cohort studies. Bone. 84. 52–56. 19 indexed citations

18.

Wu, Di, et al.. (2014). A preliminary report on oral fat tolerance test in rhesus monkeys. Lipids in Health and Disease. 13(1). 11–11. 5 indexed citations

19.

Yue, Feng, Chunling Lu, Yi Ai, Piu Chan, & Zhiming Zhang. (2014). Age-associated changes of cerebrospinal fluid amyloid-β and tau in cynomolgus monkeys. Neurobiology of Aging. 35(7). 1656–1659. 17 indexed citations

20.

Wu, Di, et al.. (2011). Analysis of glucose metabolism in cynomolgus monkeys during aging. Biogerontology. 13(2). 147–155. 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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