Yan Zuo

1.4k citations
52 papers · 910 · h-index 19

Impact in

Papers in

    • Protein Kinase Regulation and GTPase Signaling 9
    • Wnt/β-catenin signaling in development and cancer 3
    • TGF-β signaling in diseases 3
    • Melanoma and MAPK Pathways 3
    • Cancer Cells and Metastasis 3

Yan Zuo

49 papers receiving 904 citations

Peers

Yan Zuo
Comparison fields: 5 of 101
  • Cancer Research 181
  • Molecular Medicine 35
  • Molecular Biology 436
  • Oncology 140
  • Cell Biology 84
Replace Yingxin Pang with:
Yingxin Pang China
Leilei Zhang China
Meng Gu China
Pantea Izadi Iran
Carmen Crivii Romania
Fangfang Lu China
Emi Nakashima Japan
Jie Guo China
Yan Zuo relative to Yingxin Pang China Yingxin Pang's profile →
Citations per field
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Yingxin Pang · 1×
Citations per year

Countries citing papers authored by Yan Zuo

Since Specialization
Citations

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

Fields of papers citing papers by Yan Zuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016130
2 201068
3 201347
4 201747
5 202044
6 201739
7 202434
8 201532
9 202032
10 201129
11 202027
12 201226
13 201825
14 201423
15 201821
16 202221
17 202120
18 202020
19 202119
20 202214

About Yan Zuo

Yan Zuo is a scholar working on Molecular Biology, Oncology, Cell Biology, Epidemiology and Molecular Medicine, having authored 52 papers that have together received 910 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (9 papers), Antibiotic Resistance in Bacteria (4 papers), Cancer Cells and Metastasis (3 papers), Wnt/β-catenin signaling in development and cancer (3 papers), TGF-β signaling in diseases (3 papers), Melanoma and MAPK Pathways (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Microtubule and mitosis dynamics (2 papers). The work is most often cited by research in Cancer Research (181 citations), Molecular Medicine (35 citations), Molecular Biology (436 citations), Oncology (140 citations) and Cell Biology (84 citations). Yan Zuo has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jeffrey A. Frost, Wonkyung Oh, Arzu Ulu, Jeffrey T. Chang, Heather S. Carr, Zhongxin Wang, Zhi Tan, Xiaoling Chen, Weina Zhao and Yuanhong Xu. Their work appears in journals such as Journal of Medical Internet Research, Journal of Medical Virology, BMJ Open, Molecular and Cellular Biology and Journal of Cell Science.

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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