Yanxia Fu

847 citations
36 papers · 615 · h-index 15

Impact in

Papers in

    • Plant Gene Expression Analysis 3
    • IL-33, ST2, and ILC Pathways 3
    • Immune Cell Function and Interaction 3
    • Psoriasis: Treatment and Pathogenesis 2

Yanxia Fu

34 papers receiving 612 citations

Peers

Yanxia Fu
Comparison fields: 5 of 100
  • Cancer Research 77
  • Genetics 38
  • Molecular Biology 254
  • Pharmacology 29
  • Immunology 67
Replace Caleigh M. Azumaya with:
Caleigh M. Azumaya United States
Aarne Fleischer Spain
Jonathan A. Rose United States
Yoshihiro Suzuki‐Karasaki Japan
В. Н. Большаков United Kingdom
Weida Huang China
Ziping Qi China
Anna De Gaetano Italy
Nan Hao Australia
Yanxia Fu relative to Caleigh M. Azumaya United States Caleigh M. Azumaya's profile →
Citations per field
00.5×1.5×2.2×
Caleigh M. Azumaya · 1×
Citations per year

Countries citing papers authored by Yanxia Fu

Since Specialization
Citations

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

Fields of papers citing papers by Yanxia Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202371
2 201943
3 201639
4 202135
5 201431
6 201429
7 201629
8 202428
9 201927
10 201326
11 201324
12 202223
13 201721
14 201816
15 202515
16 202214
17 201514
18 201914
19 201613
20 201413

About Yanxia Fu

Yanxia Fu is a scholar working on Molecular Biology, Immunology, Plant Science, Cancer Research and Genetics, having authored 36 papers that have together received 615 indexed citations. Recurring topics across this work include Mesenchymal stem cell research (4 papers), IL-33, ST2, and ILC Pathways (3 papers), Plant Molecular Biology Research (3 papers), Plant Gene Expression Analysis (3 papers), Plant Stress Responses and Tolerance (3 papers), Immune Cell Function and Interaction (3 papers), Rheumatoid Arthritis Research and Therapies (2 papers) and Psoriasis: Treatment and Pathogenesis (2 papers). The work is most often cited by research in Cancer Research (77 citations), Genetics (38 citations), Molecular Biology (254 citations), Pharmacology (29 citations) and Immunology (67 citations). Yanxia Fu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Qun Wei, Yinyin Wang, Fangli Ren, Yanping Zhu, Ronghui Yang, Zihao Guo, Guangdong Wang, Binghui Li, Mengqi Wang and Xuexue Li. Their work appears in journals such as PLoS ONE, Nature Cell Biology, Cell Biochemistry and Function, Nature Communications and FEBS Letters.

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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