Xiaoya Fei

406 citations
34 papers · 273 · h-index 10

Impact in

Papers in

    • Psoriasis: Treatment and Pathogenesis 8
    • T-cell and B-cell Immunology 2
    • Immune Cell Function and Interaction 2

Xiaoya Fei

31 papers receiving 272 citations

Peers

Xiaoya Fei
Comparison fields: 5 of 63
  • Rehabilitation 32
  • Complementary and alternative medicine 35
  • Dermatology 35
  • Immunology 80
  • Pharmaceutical Science 16
Replace Meng Xing with:
Meng Xing China
Yosuke Morimoto Japan
Jung A. Seo South Korea
Valerio Donato Italy
Liang‐Cai Wu China
Omar Abu-Azzam Egypt
Hongmei Piao China
Eltjo J. Glazenburg Netherlands
Jianyong Zhang China
Wenrui Lin China
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Citations per field
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Meng Xing · 1×
Citations per year

Countries citing papers authored by Xiaoya Fei

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoya Fei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201940
2 202332
3 202319
4 202417
5 202214
6 202214
7 202214
8 202313
9 202512
10 201910
11 20219
12 20249
13 20207
14
Gene set enrichment analysis and ingenuity pathway analysis to verify the impact of Wnt signaling in psoriasis treated with Taodan granules.
20237
15 20227
16 20247
17 20226
18 20245
19 20235
20 20215

About Xiaoya Fei

Xiaoya Fei is a scholar working on Immunology, Molecular Biology, Dermatology, Rehabilitation and Oncology, having authored 34 papers that have together received 273 indexed citations. Recurring topics across this work include Psoriasis: Treatment and Pathogenesis (8 papers), Wound Healing and Treatments (6 papers), Dermatology and Skin Diseases (6 papers), Diabetic Foot Ulcer Assessment and Management (4 papers), Allergic Rhinitis and Sensitization (2 papers), T-cell and B-cell Immunology (2 papers), Immune Cell Function and Interaction (2 papers) and Natural Compounds in Disease Treatment (2 papers). The work is most often cited by research in Rehabilitation (32 citations), Complementary and alternative medicine (35 citations), Dermatology (35 citations), Immunology (80 citations) and Pharmaceutical Science (16 citations). Xiaoya Fei has collaborated with scholars based in China, Thailand and Belgium. Frequent co-authors include Jiankun Song, Le Kuai, Bin Li, Yue Luo, Ying Luo, Yi Ru, Jingsi Jiang, Xiaoxuan Ma, Xin Li and Qi Zheng. Their work appears in journals such as Journal of Ethnopharmacology, Evidence-based Complementary and Alternative Medicine, International Immunopharmacology, Biomaterials and Phytomedicine.

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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