Siyun Shu

1.6k total citations · 1 hit paper
27 papers, 1.5k citations indexed

About

Siyun Shu is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Siyun Shu has authored 27 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cellular and Molecular Neuroscience, 9 papers in Cognitive Neuroscience and 8 papers in Molecular Biology. Recurrent topics in Siyun Shu's work include Neuroscience and Neuropharmacology Research (6 papers), Functional Brain Connectivity Studies (4 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Siyun Shu is often cited by papers focused on Neuroscience and Neuropharmacology Research (6 papers), Functional Brain Connectivity Studies (4 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Siyun Shu collaborates with scholars based in China, Hong Kong and United States. Siyun Shu's co-authors include Lingzhi Fan, Wood Yee Chan, David T. Yew, Sau Cheung Tiu, Claus W. Heizmann, Beat W. Schäfer, Jacqueline F. McGinty, Gary M. Peterson, Lei Mo and Tingting Wang and has published in prestigious journals such as Molecular Psychiatry, Investigative Ophthalmology & Visual Science and BioMed Research International.

In The Last Decade

Siyun Shu

27 papers receiving 1.4k citations

Hit Papers

The glucose oxidase-DAB-n... 1988 2026 2000 2013 1988 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Siyun Shu China 12 647 407 273 243 205 27 1.5k
Nikolai Lazarov Bulgaria 25 628 1.0× 297 0.7× 328 1.2× 277 1.1× 435 2.1× 100 1.6k
Y. Takeuchi Japan 19 712 1.1× 336 0.8× 180 0.7× 156 0.6× 213 1.0× 65 1.3k
Hans Ericson Sweden 19 691 1.1× 622 1.5× 176 0.6× 316 1.3× 345 1.7× 32 1.8k
Laura Kus United States 14 548 0.8× 358 0.9× 318 1.2× 230 0.9× 158 0.8× 17 1.1k
John N. Armstrong Canada 21 541 0.8× 591 1.5× 215 0.8× 123 0.5× 131 0.6× 33 1.5k
Xiao‐Hong Lu United States 20 580 0.9× 745 1.8× 146 0.5× 194 0.8× 130 0.6× 37 1.7k
Zsolt Csaba France 26 468 0.7× 791 1.9× 162 0.6× 121 0.5× 210 1.0× 63 2.2k
Laurence C. Schmued United States 9 712 1.1× 263 0.6× 149 0.5× 291 1.2× 250 1.2× 9 1.2k
Cécile Viollet France 29 1.0k 1.6× 969 2.4× 265 1.0× 234 1.0× 214 1.0× 52 2.4k
Raymond H. Ho United States 21 890 1.4× 394 1.0× 294 1.1× 118 0.5× 282 1.4× 72 1.6k

Countries citing papers authored by Siyun Shu

Since Specialization
Citations

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

Fields of papers citing papers by Siyun Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siyun Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Siyun Shu. A scholar is included among the top collaborators of Siyun Shu 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 Siyun Shu. Siyun Shu 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.
Nie, Jingxin, Zengqiang Zhang, Bin Wang, et al.. (2019). Different memory patterns of digits: a functional MRI study. Journal of Biomedical Science. 26(1). 22–22. 10 indexed citations
2.
Chen, Zhiye, Xiaohong Chen, Mengqi Liu, et al.. (2016). Altered functional connectivity of the marginal division in migraine: a resting-state fMRI study. The Journal of Headache and Pain. 17(1). 89–89. 22 indexed citations
3.
Wang, Bin, Gang Jiang, Lin Ma, et al.. (2015). New learning and memory related pathways among the hippocampus, the amygdala and the ventromedial region of the striatum in rats. Journal of Chemical Neuroanatomy. 71. 13–19. 4 indexed citations
4.
Zhang, Zengqiang, Yong Liu, Bo Zhou, et al.. (2014). Altered Functional Connectivity of the Marginal Division in Alzheimer’s Disease. Current Alzheimer Research. 11(2). 145–155. 21 indexed citations
5.
Shu, Siyun, Gang Jiang, Bin Wang, et al.. (2014). The Marginal Division of the Striatum and Hippocampus Has Different Role and Mechanism in Learning and Memory. Molecular Neurobiology. 51(2). 827–839. 18 indexed citations
6.
Zeng, Changchun, Yan Yu, Siyun Shu, Xuemei Liu, & Chu‐Hua Li. (2014). Similar effects of substance P on learning and memory function between hippocampus and striatal marginal division. Neural Regeneration Research. 9(8). 857–857. 14 indexed citations
7.
Shu, Siyun, et al.. (2011). Dissociated brain organization for two-digit addition and subtraction: An fMRI investigation. Brain Research Bulletin. 86(5-6). 395–402. 17 indexed citations
8.
Chen, Xuhong, et al.. (2007). [NR2B-pERK1/2-pElk-1 signaling contributes to the avoidance learning and memory of rats].. PubMed. 23(1). 121–5. 2 indexed citations
9.
Shu, Siyun, et al.. (2005). Expression of c-fos and c-jun proteins in the marginal division of the rat striatum during learning and memory training.. PubMed. 118(5). 398–403. 1 indexed citations
10.
Shu, Siyun. (2004). A differential study on spatial learning function of the marginal division of the neostriatum and the hippocampus in the rat. 1 indexed citations
11.
Shu, Siyun, et al.. (2002). A new area in the human brain associated with learning and memory: immunohistochemical and functional MRI analysis. Molecular Psychiatry. 7(9). 1018–1022. 19 indexed citations
12.
Shu, Siyun, et al.. (2002). [Distribution of substance P and its receptor in the marginal division of rat striatum and its association with the function of learning and memory].. PubMed. 22(2). 102–6. 1 indexed citations
13.
Wang, Hong, et al.. (2002). [Expression of immediate-early genes c-fos and c-jun in the marginal division of striatum during learning and memory].. PubMed. 22(1). 9–12. 1 indexed citations
14.
Shu, Siyun, et al.. (2002). [Functional connection between the marginal division and hippocampus in rats].. PubMed. 22(8). 684–6. 1 indexed citations
15.
Wu, Yongming, Siyun Shu, Xinmin Bao, et al.. (2002). [Role of the marginal division of human neostriatum in working memory capacity for numbers received through hearing: a functional magnetic resonance imaging study].. PubMed. 22(12). 1096–8. 2 indexed citations
16.
Tiu, Sau Cheung, Wood Yee Chan, Claus W. Heizmann, et al.. (2000). Differential expression of S100B and S100A61 in the human fetal and aged cerebral cortex. Developmental Brain Research. 119(2). 159–168. 61 indexed citations
17.
Ji, Aimin, et al.. (1999). Expression of recombinant rat Neurotrophin-3 in Chinese hamster ovary cells. Science in China Series C Life Sciences. 42(6). 655–662. 1 indexed citations
18.
Shu, Siyun, et al.. (1997). Distribution of neurotensin and somatostatin immunoreactivity in the marginal division of the rat striatum. 6(1). 1–5. 4 indexed citations
19.
Shu, Siyun, Jacqueline F. McGinty, & Gary M. Peterson. (1990). High density of zinc-containing and dynorphin B- and substance P-immunoreactive terminals in the marginal division of the rat striatum. Brain Research Bulletin. 24(2). 201–205. 28 indexed citations
20.
Shu, Siyun, et al.. (1988). The glucose oxidase-DAB-nickel method in peroxidase histochemistry of the nervous system. Neuroscience Letters. 85(2). 169–171. 1154 indexed citations breakdown →

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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