Hong‐Yuan Chu

1.1k total citations · 1 hit paper
26 papers, 611 citations indexed

About

Hong‐Yuan Chu is a scholar working on Cellular and Molecular Neuroscience, Neurology and Molecular Biology. According to data from OpenAlex, Hong‐Yuan Chu has authored 26 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Cellular and Molecular Neuroscience, 15 papers in Neurology and 6 papers in Molecular Biology. Recurrent topics in Hong‐Yuan Chu's work include Neuroscience and Neuropharmacology Research (15 papers), Neurological disorders and treatments (14 papers) and Parkinson's Disease Mechanisms and Treatments (9 papers). Hong‐Yuan Chu is often cited by papers focused on Neuroscience and Neuropharmacology Research (15 papers), Neurological disorders and treatments (14 papers) and Parkinson's Disease Mechanisms and Treatments (9 papers). Hong‐Yuan Chu collaborates with scholars based in United States, China and Switzerland. Hong‐Yuan Chu's co-authors include Xuechu Zhen, Jeremy F. Atherton, Mark D. Bevan, Eitan Friedman, Guo-Zhang Jin, David L. Wokosin, D. James Surmeier, Wataru Ito, Alexei Morozov and Jiayang Li and has published in prestigious journals such as Neuron, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Hong‐Yuan Chu

24 papers receiving 608 citations

Hit Papers

Global Burden of Cardiova... 2025 2026 2025 5 10 15
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. Global Burden of Cardiovascular Diseases and its Risk Factors, 1990–2021: A Systematic Analysis for the Global Burden of Disease Study 2021
    2025 18 citations Hong‐Yuan Chu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hong‐Yuan Chu United States 14 406 245 130 110 62 26 611
Daniel Andersson Sweden 9 414 1.0× 324 1.3× 132 1.0× 71 0.6× 36 0.6× 13 845
Ulises Coffeen Mexico 14 256 0.6× 82 0.3× 103 0.8× 109 1.0× 63 1.0× 30 538
María José Sánchez-Catalán Spain 15 472 1.2× 53 0.2× 204 1.6× 158 1.4× 28 0.5× 24 663
Stanisław Wolfarth Poland 14 421 1.0× 165 0.7× 178 1.4× 96 0.9× 33 0.5× 28 568
Fabio Carletti Italy 13 233 0.6× 57 0.2× 123 0.9× 80 0.7× 132 2.1× 25 505
G. Schulze Germany 15 209 0.5× 110 0.4× 134 1.0× 51 0.5× 31 0.5× 39 477
Zhao‐Fu Sheng China 15 93 0.2× 78 0.3× 105 0.8× 150 1.4× 73 1.2× 26 512
C.A. da-Silva Brazil 13 222 0.5× 168 0.7× 99 0.8× 29 0.3× 66 1.1× 15 448
Wacław Kolasiewicz Poland 12 376 0.9× 117 0.5× 129 1.0× 92 0.8× 90 1.5× 35 480

Countries citing papers authored by Hong‐Yuan Chu

Since Specialization
Citations

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

Fields of papers citing papers by Hong‐Yuan Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong‐Yuan Chu. 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 Hong‐Yuan Chu. The network helps show where Hong‐Yuan Chu may publish in the future.

Co-authorship network of co-authors of Hong‐Yuan Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Hong‐Yuan Chu. A scholar is included among the top collaborators of Hong‐Yuan Chu 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 Hong‐Yuan Chu. Hong‐Yuan Chu 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.
Chu, Hong‐Yuan, et al.. (2025). Motor cortical neuronal hyperexcitability associated with α-synuclein aggregation. npj Parkinson s Disease. 11(1). 18–18. 2 indexed citations
2.
Chu, Hong‐Yuan, et al.. (2024). Open-source platform for kinematic analysis of mouse forelimb movement. STAR Protocols. 5(3). 103140–103140.
3.
Chu, Hong‐Yuan. (2024). Motor cortical circuit adaptations in parkinsonism. Neural Regeneration Research. 19(10). 2107–2108. 1 indexed citations
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5.
Chu, Hong‐Yuan, Yoland Smith, William W. Lytton, et al.. (2024). Dysfunction of motor cortices in Parkinson’s disease. Cerebral Cortex. 34(7). 8 indexed citations
6.
Zhou, Wei, et al.. (2024). α-Synuclein aggregation decreases cortico-amygdala connectivity and impairs social behavior in mice. Neurobiology of Disease. 202. 106702–106702. 2 indexed citations
7.
Zhou, Wei & Hong‐Yuan Chu. (2024). Progressive noradrenergic degeneration and motor cortical dysfunction in Parkinson’s disease. Acta Pharmacologica Sinica. 46(4). 829–835. 1 indexed citations
8.
Chu, Hong‐Yuan, et al.. (2023). Reduced thalamic excitation to motor cortical pyramidal tract neurons in parkinsonism. Science Advances. 9(34). eadg3038–eadg3038. 10 indexed citations
9.
Chu, Hong‐Yuan, et al.. (2023). Antiseizure medications for idiopathic generalized epilepsies: a systematic review and network meta-analysis. Journal of Neurology. 270(10). 4713–4728. 8 indexed citations
10.
Meyerdirk, Lindsay, Jennifer A. Steiner, Martha L. Escobar Galvis, et al.. (2022). Synaptic location is a determinant of the detrimental effects of α-synuclein pathology to glutamatergic transmission in the basolateral amygdala. eLife. 11. 21 indexed citations
11.
Kim, Yerim, et al.. (2021). Cell Type-Specific Decrease of the Intrinsic Excitability of Motor Cortical Pyramidal Neurons in Parkinsonism. Journal of Neuroscience. 41(25). 5553–5565. 20 indexed citations
12.
Atherton, Jeremy F., Hong‐Yuan Chu, Jyothisri Kondapalli, et al.. (2019). Maladaptive Downregulation of Autonomous Subthalamic Nucleus Activity following the Loss of Midbrain Dopamine Neurons. Cell Reports. 28(4). 992–1002.e4. 24 indexed citations
13.
Chu, Hong‐Yuan, et al.. (2017). Loss of Hyperdirect Pathway Cortico-Subthalamic Inputs Following Degeneration of Midbrain Dopamine Neurons. Neuron. 95(6). 1306–1318.e5. 91 indexed citations
14.
Chu, Hong‐Yuan, Jeremy F. Atherton, David L. Wokosin, D. James Surmeier, & Mark D. Bevan. (2015). Heterosynaptic Regulation of External Globus Pallidus Inputs to the Subthalamic Nucleus by the Motor Cortex. Neuron. 85(2). 364–376. 93 indexed citations
15.
Chu, Hong‐Yuan, Wataru Ito, Jiayang Li, & Alexei Morozov. (2012). Target-Specific Suppression of GABA Release from Parvalbumin Interneurons in the Basolateral Amygdala by Dopamine. Journal of Neuroscience. 32(42). 14815–14820. 43 indexed citations
16.
Chu, Hong‐Yuan, Shanglin Zhou, Xiaohua Cao, et al.. (2011). SKF83959 suppresses excitatory synaptic transmission in rat hippocampus via a dopamine receptor‐independent mechanism. Journal of Neuroscience Research. 89(8). 1259–1266. 17 indexed citations
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Chu, Hong‐Yuan, Guo-Zhang Jin, Eitan Friedman, & Xuechu Zhen. (2007). Recent Development in Studies of Tetrahydroprotoberberines: Mechanism in Antinociception and Drug Addiction. Cellular and Molecular Neurobiology. 28(4). 491–499. 127 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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