Chia-Hsien Wu

441 total citations
15 papers, 254 citations indexed

About

Chia-Hsien Wu is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Chia-Hsien Wu has authored 15 papers receiving a total of 254 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Neurology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Chia-Hsien Wu's work include Vagus Nerve Stimulation Research (4 papers), Receptor Mechanisms and Signaling (4 papers) and Nicotinic Acetylcholine Receptors Study (4 papers). Chia-Hsien Wu is often cited by papers focused on Vagus Nerve Stimulation Research (4 papers), Receptor Mechanisms and Signaling (4 papers) and Nicotinic Acetylcholine Receptors Study (4 papers). Chia-Hsien Wu collaborates with scholars based in Japan, United States and Taiwan. Chia-Hsien Wu's co-authors include Yoshio Nakamura, Tsuyoshi Inoue, Reiko Inagi, Masaomi Nangaku, Tetsuhiro Tanaka, Hiroshi Maekawa, Mai Sugahara, Yu Ishimoto, Tzu‐Ming Jao and Chih‐Kang Chiang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Brain Research.

In The Last Decade

Chia-Hsien Wu

14 papers receiving 252 citations

Peers

Chia-Hsien Wu
Comparison fields: 5 of 66
  • Molecular Biology 87
  • Nephrology 52
  • Physiology 46
  • Epidemiology 40
  • Cell Biology 38
Replace Anna Hammer with:
Anna Hammer Germany
Mark D. Okusa United States
Kei Miyanaka Japan
Yanhong Tang China
Haibo Tan China
Jingjing Liang China
Sonja Brosel United States
Min Ji Sung South Korea
Dóra Balogh Hungary
Kenzo Iino Japan
Anna Hammer Germany View profile →
Citations per field, relative to Chia-Hsien Wu
Chia-Hsien Wu · 1×
Citations per year, relative to Chia-Hsien Wu
Chia-Hsien Wu · 1×

Countries citing papers authored by Chia-Hsien Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chia-Hsien Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia-Hsien Wu. 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 Chia-Hsien Wu. The network helps show where Chia-Hsien Wu may publish in the future.

Co-authorship network of co-authors of Chia-Hsien Wu

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

All Works

15 of 15 papers shown
# Work Indexed citations
1 1
2 2
3 4
4 0
5 3
6 18
7 3
8 14
9 3
10 20
11 14
12 107
13 23
14 9
15 33

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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2026