Shu-Ming Huang

3.0k total citations · 1 hit paper
22 papers, 2.2k citations indexed

About

Shu-Ming Huang is a scholar working on Cellular and Molecular Neuroscience, Physiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Shu-Ming Huang has authored 22 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cellular and Molecular Neuroscience, 8 papers in Physiology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Shu-Ming Huang's work include Alzheimer's disease research and treatments (8 papers), Neuroscience and Neuropharmacology Research (7 papers) and Stress Responses and Cortisol (4 papers). Shu-Ming Huang is often cited by papers focused on Alzheimer's disease research and treatments (8 papers), Neuroscience and Neuropharmacology Research (7 papers) and Stress Responses and Cortisol (4 papers). Shu-Ming Huang collaborates with scholars based in China, Japan and United States. Shu-Ming Huang's co-authors include Nobuhisa Iwata, Takaomi C. Saido, Makoto Higuchi, Tetsuya Suhara, Bin Zhang, Virginia M.‐Y. Lee, John Q. Trojanowski, Jun Maeda, Yasumasa Yoshiyama and Jiro Takano and has published in prestigious journals such as Nature Medicine, Neuron and Journal of Ethnopharmacology.

In The Last Decade

Shu-Ming Huang

22 papers receiving 2.2k citations

Hit Papers

Synapse Loss and Microglial Activation Precede Tangles in... 2007 2026 2013 2019 2007 500 1000 1.5k
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. Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy Mouse Model
    2007 1.6k citations Yasumasa Yoshiyama, Makoto Higuchi et al. Neuron profile →

Peers

Shu-Ming Huang
Estibaliz Capetillo‐Zarate Spain
Amy M. Pooler United Kingdom
Jennifer Paulson United States
Tina L. Beckett United States
Binggui Sun China
Lih-Fen Lue United States
Fabien Delerue Australia
Tritia R. Yamasaki United States
Mian Bi Australia
Amadeus Gladbach Australia
Estibaliz Capetillo‐Zarate Spain
Shu-Ming Huang
Citations per year, relative to Shu-Ming Huang Shu-Ming Huang (= 1×) peers Estibaliz Capetillo‐Zarate

Countries citing papers authored by Shu-Ming Huang

Since Specialization
Citations

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

Fields of papers citing papers by Shu-Ming Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu-Ming Huang. 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 Shu-Ming Huang. The network helps show where Shu-Ming Huang may publish in the future.

Co-authorship network of co-authors of Shu-Ming Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Shu-Ming Huang. A scholar is included among the top collaborators of Shu-Ming Huang 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 Shu-Ming Huang. Shu-Ming Huang 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.
Wu, Dan, Bo Zhang, Yung‐Yee Chang, & Shu-Ming Huang. (2024). Apathy Associated with Alzheimer's Disease. Current Alzheimer Research. 21(8). 527–537. 2 indexed citations
2.
3.
Kong, Fanyi, et al.. (2023). Pathogenesis of Depression in Alzheimer’s Disease. Neurochemical Research. 49(3). 548–556. 9 indexed citations
4.
Yang, Ye, Bo Zhang, Yan Li, et al.. (2022). Yin Huo Tang, a traditional Chinese herbal formula, relives ovariectomy and empty bottle stimulation-induced menopause-like symptoms in mice. Frontiers in Endocrinology. 13. 994642–994642. 3 indexed citations
5.
Huang, Shu-Ming, et al.. (2022). Biological Deciphering of the “Kidney Governing Bones” Theory in Traditional Chinese Medicine. Evidence-based Complementary and Alternative Medicine. 2022. 1–8. 12 indexed citations
6.
Wang, Na, et al.. (2020). Kai‐Xin‐San, a Chinese Herbal Decoction, Accelerates the Degradation of β‐Amyloid by Enhancing the Expression of Neprilysin in Rats. Evidence-based Complementary and Alternative Medicine. 2020(1). 3862342–3862342. 7 indexed citations
7.
Tian, Ming, et al.. (2020). Advances in phytochemical and modern pharmacological research of Rhizoma Corydalis. Pharmaceutical Biology. 58(1). 265–275. 72 indexed citations
8.
Cui, Yu, et al.. (2020). Androgen deficit changes the response to antidepressant drugs in tail suspension test in mice. The Aging Male. 23(5). 1259–1265. 7 indexed citations
9.
Li, Wěi, et al.. (2019). Long-term estrogen deprivation changes the response to antianxiety drugs in mice in the elevated plus maze test. Gynecological Endocrinology. 35(12). 1054–1058. 5 indexed citations
10.
Zhang, Bo, et al.. (2018). Postsynaptic GluR2 Involved in Amelioration of Aβ-Induced Memory Dysfunction by KAIXIN-San Through Rescuing Hippocampal LTP in Mice. Rejuvenation Research. 22(2). 131–137. 13 indexed citations
11.
Yang, Ye, Cun‐Zhi Liu, Yu-Wei Zhang, et al.. (2018). A new animal model for menopausal transition: combination of ovariectomy and empty bottle stimulation. Gynecological Endocrinology. 34(10). 840–844. 4 indexed citations
12.
13.
Yang, Ye, et al.. (2016). Ovariectomy changes the response to antidepressant drugs in tail suspension test in mice. Gynecological Endocrinology. 32(12). 986–990. 6 indexed citations
14.
Zhang, Bo, et al.. (2016). An applicable method of drawing cerebrospinal fluid in rats. Journal of Chemical Neuroanatomy. 74. 18–20. 6 indexed citations
15.
Wang, Qiuhong, Changfu Wang, Zunpeng Shu, et al.. (2013). Valeriana amurensis improves Amyloid-beta 1-42 induced cognitive deficit by enhancing cerebral cholinergic function and protecting the brain neurons from apoptosis in mice. Journal of Ethnopharmacology. 153(2). 318–325. 39 indexed citations
16.
Zhang, Bo, Wen Wei, Shuang Liu, et al.. (2012). The comparison of three methods of drawing cerebrospinal fluid in rabbit. Journal of Neuroscience Methods. 209(2). 398–402. 8 indexed citations
17.
Nakajima, Ryuichi, Keizo Takao, Shu-Ming Huang, et al.. (2008). Comprehensive behavioral phenotyping of calpastatin-knockout mice. Molecular Brain. 1(1). 7–7. 40 indexed citations
18.
Yoshiyama, Yasumasa, Makoto Higuchi, Bin Zhang, et al.. (2007). Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy Mouse Model. Neuron. 54(2). 343–344. 40 indexed citations
19.
Yoshiyama, Yasumasa, Makoto Higuchi, Bin Zhang, et al.. (2007). Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy Mouse Model. Neuron. 53(3). 337–351. 1600 indexed citations breakdown →
20.
Saito, Takashi, Nobuhisa Iwata, Satoshi Tsubuki, et al.. (2005). Somatostatin regulates brain amyloid β peptide Aβ42 through modulation of proteolytic degradation. Nature Medicine. 11(4). 434–439. 302 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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