Gui‐Ying Zan

458 citations
21 papers · 336 · h-index 12

Impact in

Papers in

Gui‐Ying Zan

20 papers receiving 334 citations

Peers

Gui‐Ying Zan
Comparison fields: 5 of 60
  • Behavioral Neuroscience 38
  • Biological Psychiatry 25
  • Cellular and Molecular Neuroscience 166
  • Physiology 60
  • Cognitive Neuroscience 40
Replace Gali Umschweif with:
Gali Umschweif Israel
María B. Carreira Panama
Jessica A. Siegel United States
Sherry X. Lu United States
Elayne Vieira Dias Brazil
Amy DiCamillo United States
Ana David-Pereira Portugal
Ana Domi Sweden
В. Б. Наркевич Russia
Vorani S. Ramachandra United States
Gui‐Ying Zan relative to Gali Umschweif Israel Gali Umschweif's profile →
Citations per field
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Citations per year

Countries citing papers authored by Gui‐Ying Zan

Since Specialization
Citations

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

Fields of papers citing papers by Gui‐Ying Zan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gui‐Ying Zan. 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 Gui‐Ying Zan. The network helps show where Gui‐Ying Zan may publish in the future.

Co-authors

The 25 scholars most cited alongside Gui‐Ying Zan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gui‐Ying Zan Line = papers co-authored together Gui‐Ying Zan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201845
2 202336
3 201527
4 202327
5 201623
6 201621
7 202120
8 201719
9 201618
10 202118
11 202017
12 202216
13 202112
14 201611
15 201810
16 20157
17 20255
18 20252
19 20251
20 20251

About Gui‐Ying Zan

Gui‐Ying Zan is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Behavioral Neuroscience, Molecular Biology and Neurology, having authored 21 papers that have together received 336 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (9 papers), Neuropeptides and Animal Physiology (7 papers), Neurotransmitter Receptor Influence on Behavior (6 papers), Neuroscience and Neuropharmacology Research (5 papers), Neuroendocrine regulation and behavior (3 papers), Memory and Neural Mechanisms (2 papers), Stress Responses and Cortisol (2 papers) and Transcranial Magnetic Stimulation Studies (1 paper). The work is most often cited by research in Behavioral Neuroscience (38 citations), Biological Psychiatry (25 citations), Cellular and Molecular Neuroscience (166 citations), Physiology (60 citations) and Cognitive Neuroscience (40 citations). Gui‐Ying Zan has collaborated with scholars based in China. Frequent co-authors include Jing‐Gen Liu, Yujun Wang, Xiaohong H. Shu, Min Zhao, Yao Liu, Qian Wang, Weijia Du, Yuchen Lu, Dong Hu and Zhiqiang Liu. Their work appears in journals such as Behavioural Brain Research, Molecular Psychiatry, Neuroscience, Acta Pharmacologica Sinica and Neuron.

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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