Haitong Wan

914 total citations
48 papers, 729 citations indexed

About

Haitong Wan is a scholar working on Complementary and alternative medicine, Neurology and Pharmacology. According to data from OpenAlex, Haitong Wan has authored 48 papers receiving a total of 729 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Complementary and alternative medicine, 19 papers in Neurology and 16 papers in Pharmacology. Recurrent topics in Haitong Wan's work include Traditional Chinese Medicine Analysis (41 papers), Neurological Disease Mechanisms and Treatments (17 papers) and Biological and pharmacological studies of plants (9 papers). Haitong Wan is often cited by papers focused on Traditional Chinese Medicine Analysis (41 papers), Neurological Disease Mechanisms and Treatments (17 papers) and Biological and pharmacological studies of plants (9 papers). Haitong Wan collaborates with scholars based in China and United States. Haitong Wan's co-authors include Jiehong Yang, Yu He, Huifen Zhou, Li Yu, Chang Li, Wei Fu, Tao Zhao, Yuyan Zhang, Chongyu Shao and Fei Yin and has published in prestigious journals such as Brain Research, Neuroscience and Journal of Ethnopharmacology.

In The Last Decade

Haitong Wan

47 papers receiving 720 citations

Peers

Haitong Wan
Comparison fields: 5 of 94
  • Complementary and alternative medicine 347
  • Molecular Biology 332
  • Neurology 251
  • Pharmacology 117
  • Pharmacology 94
Chongyu Shao China
Luchen Shan China
John Orgah China
Jianxun Liu China
Guibo Sun China
Li Yan China
Jinyi Cao China
Bai‐He Hu China
Lixia Xie China
Chongyu Shao China View profile →
Citations per field, relative to Haitong Wan
Haitong Wan · 1×
Citations per year, relative to Haitong Wan
Haitong Wan · 1×

Countries citing papers authored by Haitong Wan

Since Specialization
Citations

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

Fields of papers citing papers by Haitong Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haitong Wan

This figure shows the co-authorship network connecting the top 25 collaborators of Haitong Wan. A scholar is included among the top collaborators of Haitong 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 Haitong Wan. Haitong 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
# Work Indexed citations
1 5
2 2
3 7
4 3
5 32
6 3
7 12
8 5
9 18
10 21
11 38
12 18
13 38
14 30
15 11
16
Transport characteristics of ligustrazine across Caco-2 cell monolayer model and its effect on P-glycoprotein expression
1
17
Research on the compatibility of Chinese medicine compound based on structure equation model-taking Lingguizhugan decoction as an example
1
18 93
19 53
20
Establishment of artificial blood-brain barrier and its permeability affected by tetramethylpyrazine combined with puerarin
1

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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