Da Fu

7.1k total citations · 1 hit paper
165 papers, 5.0k citations indexed

About

Da Fu is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Da Fu has authored 165 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Molecular Biology, 66 papers in Cancer Research and 41 papers in Oncology. Recurrent topics in Da Fu's work include MicroRNA in disease regulation (38 papers), Cancer-related molecular mechanisms research (34 papers) and Circular RNAs in diseases (28 papers). Da Fu is often cited by papers focused on MicroRNA in disease regulation (38 papers), Cancer-related molecular mechanisms research (34 papers) and Circular RNAs in diseases (28 papers). Da Fu collaborates with scholars based in China, United States and Tanzania. Da Fu's co-authors include Yu‐Shui Ma, Xizhong Shen, Ting Yu, Ying Fang, Cui Sun, Zhongwei Lv, Wen Li, Xiaodong Zheng, Jibin Liu and Yi Shi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Clinical Investigation.

In The Last Decade

Da Fu

161 papers receiving 4.9k citations

Hit Papers

Liquid biopsy in lung cancer: significance in diagnostics... 2022 2026 2023 2024 2022 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Da Fu China 40 3.1k 1.9k 922 567 469 165 5.0k
Jianjun Shen United States 45 4.4k 1.4× 1.3k 0.7× 1.4k 1.5× 610 1.1× 635 1.4× 151 6.6k
Zhe Zhang China 35 3.0k 0.9× 1.6k 0.8× 451 0.5× 494 0.9× 286 0.6× 162 4.6k
Alexander T.H. Wu Taiwan 40 2.6k 0.8× 1.1k 0.6× 1.1k 1.2× 484 0.9× 684 1.5× 170 5.1k
Bin Yan China 38 2.8k 0.9× 1.5k 0.8× 899 1.0× 692 1.2× 876 1.9× 179 4.9k
Asako Nakamura Japan 30 4.1k 1.3× 1.4k 0.7× 1.5k 1.6× 266 0.5× 718 1.5× 97 5.7k
Lijuan Wang China 36 2.6k 0.8× 1.9k 1.0× 968 1.0× 372 0.7× 344 0.7× 146 4.4k
Gong Yang China 45 2.8k 0.9× 1.5k 0.8× 1.4k 1.6× 625 1.1× 461 1.0× 108 5.0k
Adam Ertel United States 35 2.6k 0.8× 1.4k 0.8× 1.6k 1.7× 500 0.9× 818 1.7× 71 4.5k
Yuan Fang China 33 3.0k 0.9× 1.1k 0.6× 688 0.7× 642 1.1× 510 1.1× 127 4.1k
Limin Liu China 39 3.1k 1.0× 828 0.4× 650 0.7× 556 1.0× 420 0.9× 167 5.2k

Countries citing papers authored by Da Fu

Since Specialization
Citations

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

Fields of papers citing papers by Da Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Da Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Da Fu. A scholar is included among the top collaborators of Da Fu 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 Da Fu. Da Fu 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
1.
Li, Ming O., et al.. (2024). Immune Regulatory Networks and Therapy of γδ T Cells in Liver Cancer: Recent Trends and Advancements. Journal of Clinical and Translational Hepatology. 0(0). 0–0. 4 indexed citations
2.
Gao, Xia, Yang Liu, Shuyu Zhai, et al.. (2024). H19 promotes polarization and alternative splicing in tumor-associated macrophages, facilitating pancreatic cancer progression. Cancer Letters. 611. 217389–217389. 6 indexed citations
3.
Wang, Hao, Fan Cui, Qianqian Song, et al.. (2023). Enhancing prognostic accuracy in head and neck squamous cell carcinoma chemotherapy via a lipid metabolism-related clustered polygenic model. Cancer Cell International. 23(1). 164–164. 4 indexed citations
4.
Dou, Xuefeng, Qiang Fu, Qilai Long, et al.. (2023). PDK4-dependent hypercatabolism and lactate production of senescent cells promotes cancer malignancy. Nature Metabolism. 5(11). 1887–1910. 88 indexed citations
5.
Li, Sha, Pei Xue, Kun Ye, et al.. (2023). Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma. Journal of Advanced Research. 54. 133–146. 12 indexed citations
6.
Liu, Jibin, et al.. (2022). Current Status and Prospects of Clinical Treatment of Osteosarcoma. Technology in Cancer Research & Treatment. 21. 2213866584–2213866584. 42 indexed citations
7.
He, Jintao, Weidong Bai, Qinlu Lin, et al.. (2021). Cross-kingdom regulation by dietary plant miRNAs: an evidence-based review with recent updates. Food & Function. 12(20). 9549–9562. 24 indexed citations
8.
Li, Wen, Yu Liu, Yi Shi, et al.. (2021). Unravelling the Role of LncRNA WT1-AS/miR-206/NAMPT Axis as Prognostic Biomarkers in Lung Adenocarcinoma. Biomolecules. 11(2). 203–203. 20 indexed citations
9.
Tian, Linlin, Bin Qian, Xiaohui Jiang, et al.. (2021). MicroRNA-497-5p Is Downregulated in Hepatocellular Carcinoma and Associated with Tumorigenesis and Poor Prognosis in Patients. International Journal of Genomics. 2021. 1–16. 12 indexed citations
10.
Ma, Yu‐Shui, Bowen Shi, Haimin Lu, et al.. (2021). MicroRNA-499 serves as a sensitizer for lung cancer cells to radiotherapy by inhibition of CK2α-mediated phosphorylation of p65. Molecular Therapy — Oncolytics. 21. 171–182. 4 indexed citations
11.
Zhang, Jiajia, Yu‐Shui Ma, Yi Shi, et al.. (2021). Identified GNGT1 and NMU as Combined Diagnosis Biomarker of Non-Small-Cell Lung Cancer Utilizing Bioinformatics and Logistic Regression. Disease Markers. 2021. 1–14. 15 indexed citations
12.
Liu, Min, Tongyu Sun, Ni Li, et al.. (2019). BRG1 attenuates colonic inflammation and tumorigenesis through autophagy-dependent oxidative stress sequestration. Nature Communications. 10(1). 4614–4614. 77 indexed citations
13.
Li, Wen, Yu‐Shui Ma, Qinlu Lin, & Da Fu. (2019). Deep Processing of Rice and Comprehensive Utilization of Its By-products. Journal of Food and Nutrition Research. 7(5). 370–376. 3 indexed citations
14.
Ma, Yu‐Shui, Fei Yu, Xiaoming Zhong, et al.. (2018). miR-30 Family Reduction Maintains Self-Renewal and Promotes Tumorigenesis in NSCLC-Initiating Cells by Targeting Oncogene TM4SF1. Molecular Therapy. 26(12). 2751–2765. 35 indexed citations
15.
Zhao, Yuan, Yu‐Shui Ma, Ying Fang, et al.. (2011). IGF2BP2 Genetic Variation and Type 2 Diabetes: A Global Meta-Analysis. DNA and Cell Biology. 31(5). 713–720. 15 indexed citations
16.
Liu, Li‐Li, Da Fu, Yu‐Shui Ma, & Xizhong Shen. (2011). The Power and the Promise of Liver Cancer Stem Cell Markers. Stem Cells and Development. 20(12). 2023–2030. 67 indexed citations
17.
Fu, Da. (2010). Two New Species of Yulania Spach from Sichuan Province of China. Zhiwu yanjiu. 3 indexed citations
18.
Fu, Da. (2010). A New Species of Armeniaca Scop. from China. Zhiwu yanjiu. 6 indexed citations
19.
Fu, Da. (2002). New Viewpoints on the Species of Xinyi and Mulan. JOURNAL OF WUHAN BOTANICAL RESEARCH.
20.
Fu, Da. (2001). Notes on Yulania Spach. JOURNAL OF WUHAN BOTANICAL RESEARCH. 5 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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