Fayong Hu

875 total citations · 1 hit paper
12 papers, 563 citations indexed

About

Fayong Hu is a scholar working on Cancer Research, Oncology and Nuclear and High Energy Physics. According to data from OpenAlex, Fayong Hu has authored 12 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cancer Research, 3 papers in Oncology and 3 papers in Nuclear and High Energy Physics. Recurrent topics in Fayong Hu's work include MicroRNA in disease regulation (4 papers), Cancer-related molecular mechanisms research (3 papers) and Magnetic confinement fusion research (3 papers). Fayong Hu is often cited by papers focused on MicroRNA in disease regulation (4 papers), Cancer-related molecular mechanisms research (3 papers) and Magnetic confinement fusion research (3 papers). Fayong Hu collaborates with scholars based in China. Fayong Hu's co-authors include Yongdong Feng, Junbo Hu, Rongsheng Zhang, Xi Yang, Liang Liu, Xiaochao Zhang, Geng Li, Guodong Li, Bixiang Zhang and Xuelai Luo and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Fayong Hu

11 papers receiving 556 citations

Hit Papers

IL-6 regulates autophagy and chemotherapy resistance by p... 2021 2026 2022 2024 2021 50 100 150

Peers

Fayong Hu
Lin Wan China
Moshe C. Silverstein United States
Spiridon Tsavachidis United States
Yejun Qin China
Lin Wan China
Fayong Hu
Citations per year, relative to Fayong Hu Fayong Hu (= 1×) peers Lin Wan

Countries citing papers authored by Fayong Hu

Since Specialization
Citations

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

Fields of papers citing papers by Fayong Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fayong Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Fayong Hu. A scholar is included among the top collaborators of Fayong Hu 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 Fayong Hu. Fayong Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Wang, Jiayi, Fayong Hu, Jin Li, et al.. (2025). Comparative performance of multiple ensemble learning models for preoperative prediction of tumor deposits in rectal cancer based on MR imaging. Scientific Reports. 15(1). 4848–4848. 4 indexed citations
2.
Hu, Fayong, et al.. (2023). Development of the control system for electron cyclotron resonance heating on J-TEXT tokamak. Review of Scientific Instruments. 94(4).
3.
Huang, Changsheng, Fuqing Hu, Da Song, et al.. (2022). EZH2-triggered methylation of SMAD3 promotes its activation and tumor metastasis. SHILAP Revista de lepidopterología. 31 indexed citations
4.
Hu, Fuqing, Da Song, Yumeng Yan, et al.. (2021). IL-6 regulates autophagy and chemotherapy resistance by promoting BECN1 phosphorylation. Nature Communications. 12(1). 3651–3651. 168 indexed citations breakdown →
5.
Zhang, Xiaochao, Fayong Hu, Geng Li, et al.. (2018). Human colorectal cancer-derived mesenchymal stem cells promote colorectal cancer progression through IL-6/JAK2/STAT3 signaling. Cell Death and Disease. 9(2). 25–25. 171 indexed citations
6.
Zheng, Wei, et al.. (2018). J-TEXT distributed data storage and management system. Fusion Engineering and Design. 129. 207–213. 2 indexed citations
7.
Zheng, Wei, Fayong Hu, Ming Zhang, et al.. (2018). Hybrid neural network for density limit disruption prediction and avoidance on J-TEXT tokamak. Nuclear Fusion. 58(5). 56016–56016. 44 indexed citations
8.
Cao, Xiaonian, Fayong Hu, Guodong Li, et al.. (2017). miR-19a contributes to gefitinib resistance and epithelial mesenchymal transition in non-small cell lung cancer cells by targeting c-Met. Scientific Reports. 7(1). 2939–2939. 29 indexed citations
9.
Hu, Fayong, Xiaonian Cao, Qinzi Xu, et al.. (2016). miR-124 modulates gefitinib resistance through SNAI2 and STAT3 in non-small cell lung cancer. Journal of Huazhong University of Science and Technology [Medical Sciences]. 36(6). 839–845. 25 indexed citations
10.
Hu, Fayong, et al.. (2016). MiR-363-3p inhibits the epithelial-to-mesenchymal transition and suppresses metastasis in colorectal cancer by targeting Sox4. Biochemical and Biophysical Research Communications. 474(1). 35–42. 62 indexed citations
11.
Rao, Bo, et al.. (2016). Fast island phase identification for tearing mode feedback control on J-TEXT tokamak. Review of Scientific Instruments. 87(11). 11D425–11D425. 4 indexed citations
12.
Li, Xiaolan, Jianwu Jiang, Rui Yang, et al.. (2015). Expression of HAX-1 in colorectal cancer and its role in cancer cell growth. Molecular Medicine Reports. 12(3). 4071–4078. 23 indexed citations

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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