Fang Wan

2.6k citations
57 papers · 1.9k indexed · 1 hit paper · h-index 21
Topics
Parkinson's Disease Mechanisms and Treatments (10 papers)Arsenic contamination and mitigation (7 papers)Neuroinflammation and Neurodegeneration Mechanisms (5 papers)
Partner nations
ChinaUnited StatesFrance

In The Last Decade

Fang Wan

53 papers receiving 1.9k citations

Hit Papers

Weight Loss and Malnutrition in Patients with Parkinson's...20182026202020232018100200300

Peers

Fang Wan
Comparison fields: 5 of 142
  • Molecular Biology 588
  • Neurology 416
  • Cellular and Molecular Neuroscience 360
  • Neurology 350
  • Physiology 265
Replace Wenjing Luo with:
Wenjing Luo China
Jingyuan Chen China
Ju‐Hee Kang South Korea
Kimberly C. Paul United States
William Gray United Kingdom
Ayşel Ağar Türkiye
Takanori Miki Japan
Thomas S. Guillot United States
Maria Rosaria Carratù Italy
Xiaoping Wang China
Fang Wan relative to Wenjing Luo China Wenjing Luo's profile →
Citations per field
00.5×1.5×2.3×
Wenjing Luo · 1×
Citations per year

Countries citing papers authored by Fang Wan

Since Specialization
Citations

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

Fields of papers citing papers by Fang Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang Wan

This figure shows the co-authorship network connecting the top 25 collaborators of Fang Wan. A scholar is included among the top collaborators of Fang Wan 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 Fang Wan. Fang Wan 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
#WorkIndexed citations
1 13
2 0
3 5
4 1
5 3
6 3
7 14
8 68
9 100
10 22
11 137
12 35
13 18
14 16
15 116
16 2
17 1
18 7
19 10
20
Choice of the Multivariate Copulas with Parametric Structure
0

About Fang Wan

Fang Wan is a scholar working on Neurology, Environmental Chemistry and Neurology, having authored 57 papers that have together received 1.9k indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (10 papers), Arsenic contamination and mitigation (7 papers) and Neuroinflammation and Neurodegeneration Mechanisms (5 papers). The work is most often cited by research in Neurology (350 citations), Neurology (416 citations) and Biological Psychiatry (57 citations). Fang Wan has collaborated with scholars based in China, United States and France. Frequent co-authors include Nian Xiong, Yun Xia, Jinsha Huang, Gaolong Zhong, Zhaoxin Tang, Lianmei Hu, Sijia Yin, Liang Kou, Guoxin Zhang and Chao Han. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Brain.

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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