Ching‐Hsiang Wu

22 papers receiving 653 citations

Peers

Ching‐Hsiang Wu
Comparison fields: 5 of 86
  • Neurology 200
  • Biological Psychiatry 38
  • Developmental Neuroscience 58
  • Reproductive Medicine 60
  • Endocrine and Autonomic Systems 44
Replace V.A.M. Vincent with:
V.A.M. Vincent United States
John D. Inglis United Kingdom
Lilian Wikström Sweden
Hayato Matsunaga Japan
Helois Radford United Kingdom
Pamela J. Voulalas United States
Natalia Yanguas‐Casás Spain
Mary Kay Meintzer United States
Marit Pedersen Delghandi Norway
Ching‐Hsiang Wu relative to V.A.M. Vincent United States V.A.M. Vincent's profile →
Citations per field
00.5×3.7×
V.A.M. Vincent · 1×
Citations per year

Countries citing papers authored by Ching‐Hsiang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐Hsiang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching‐Hsiang 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 Ching‐Hsiang Wu. The network helps show where Ching‐Hsiang Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Ching‐Hsiang Wu, 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 Ching‐Hsiang Wu Line = papers co-authored together Ching‐Hsiang Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001117
2 2006101
3 200068
4 200965
5 200843
6 201540
7 200940
8 201533
9 201026
10 200625
11 200221
12 201014
13 200114
14 200914
15 200712
16 200511
17 200110
18 20145
19 20024
20 20094

About Ching‐Hsiang Wu

Ching‐Hsiang Wu is a scholar working on Neurology, Molecular Biology, Immunology, Surgery and Neurology, having authored 22 papers that have together received 670 indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (7 papers), Inflammation biomarkers and pathways (2 papers), Complement system in diseases (2 papers), Neonatal and fetal brain pathology (2 papers), Cell Adhesion Molecules Research (2 papers), Advanced Glycation End Products research (2 papers), Antiplatelet Therapy and Cardiovascular Diseases (2 papers) and Platelet Disorders and Treatments (2 papers). The work is most often cited by research in Neurology (200 citations), Biological Psychiatry (38 citations), Developmental Neuroscience (58 citations), Reproductive Medicine (60 citations) and Endocrine and Autonomic Systems (44 citations). Ching‐Hsiang Wu has collaborated with scholars based in Taiwan and Singapore. Frequent co-authors include Aijun Hao, Eng‐Ang Ling, Charanjit Kaur, Ching‐Chiung Wang, Kun–Ying Yen, I‐Hua Wei, Lingling Yang, Mang‐Hung Tsai, Ming‐Jia Jou and Hsiung–Fei Chien. Their work appears in journals such as Journal of Anatomy, Neuroscience Research, Thrombosis Research, Toxicology and Behavioural Brain Research.

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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