Weiming Fu

7.9k total citations · 1 hit paper
91 papers, 6.4k citations indexed

About

Weiming Fu is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Weiming Fu has authored 91 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Molecular Biology, 30 papers in Cancer Research and 17 papers in Physiology. Recurrent topics in Weiming Fu's work include Cancer-related molecular mechanisms research (21 papers), Circular RNAs in diseases (15 papers) and MicroRNA in disease regulation (14 papers). Weiming Fu is often cited by papers focused on Cancer-related molecular mechanisms research (21 papers), Circular RNAs in diseases (15 papers) and MicroRNA in disease regulation (14 papers). Weiming Fu collaborates with scholars based in China, United States and Hong Kong. Weiming Fu's co-authors include Mark P. Mattson, Hong Luo, Jinfang Zhang, Mark P. Mattson, Katsutoshi Furukawa, Weicheng Liang, Mary Miu Yee Waye, Yadong Goodman, Chengbiao Lu and Qing Guo and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Journal of Neuroscience.

In The Last Decade

Weiming Fu

88 papers receiving 6.3k citations

Hit Papers

Translation of the circular RNA circβ-catenin promotes li... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weiming Fu China 39 3.9k 1.8k 1.7k 935 628 91 6.4k
Eui‐Ju Choi South Korea 45 5.3k 1.4× 1.0k 0.6× 1.0k 0.6× 929 1.0× 920 1.5× 107 8.5k
Hong Wei China 40 2.8k 0.7× 1.1k 0.6× 1.5k 0.9× 649 0.7× 396 0.6× 146 5.6k
Varda Shoshan‐Barmatz Israel 59 9.3k 2.4× 1.4k 0.8× 1.3k 0.8× 1.7k 1.8× 843 1.3× 165 11.5k
Olivier Braissant Switzerland 40 5.4k 1.4× 794 0.4× 2.6k 1.5× 537 0.6× 1.1k 1.7× 88 8.3k
Zengqiang Yuan China 51 5.5k 1.4× 1.0k 0.6× 952 0.6× 730 0.8× 1.7k 2.6× 140 8.6k
Qiwei Zhai China 37 3.0k 0.8× 914 0.5× 1.5k 0.9× 490 0.5× 336 0.5× 86 6.0k
Ying Luo China 42 4.5k 1.2× 749 0.4× 661 0.4× 503 0.5× 808 1.3× 179 7.6k
Martin Dickens United Kingdom 24 7.1k 1.8× 1.3k 0.7× 712 0.4× 1.1k 1.2× 1.1k 1.7× 39 9.6k
Lixin Sun China 43 2.9k 0.7× 687 0.4× 497 0.3× 800 0.9× 593 0.9× 167 6.0k
Derek Yang United States 25 4.7k 1.2× 1.4k 0.8× 567 0.3× 894 1.0× 630 1.0× 40 7.4k

Countries citing papers authored by Weiming Fu

Since Specialization
Citations

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

Fields of papers citing papers by Weiming Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiming Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Weiming Fu. A scholar is included among the top collaborators of Weiming 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 Weiming Fu. Weiming 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.
Fu, Weiming, et al.. (2025). Urban real-time rainfall-runoff prediction using adaptive SSA-decomposition with dual attention. Journal of Hydrology. 653. 132701–132701. 3 indexed citations
2.
Shi, Chuan-Jian, et al.. (2021). Gallic Acid Suppressed Tumorigenesis by an LncRNA MALAT1-Wnt/β-Catenin Axis in Hepatocellular Carcinoma. Frontiers in Pharmacology. 12. 708967–708967. 24 indexed citations
3.
Liang, Weicheng, et al.. (2021). Super-enhancer-driven lncRNA-DAW promotes liver cancer cell proliferation through activation of Wnt/β-catenin pathway. Molecular Therapy — Nucleic Acids. 26. 1351–1363. 31 indexed citations
4.
Shao, Jiang, Chuan-Jian Shi, Yun Li, et al.. (2020). LincROR Mediates the Suppressive Effects of Curcumin on Hepatocellular Carcinoma Through Inactivating Wnt/β-Catenin Signaling. Frontiers in Pharmacology. 11. 847–847. 34 indexed citations
5.
Shi, Chuan-Jian, et al.. (2020). H19-Wnt/β-catenin regulatory axis mediates the suppressive effects of apigenin on tumor growth in hepatocellular carcinoma. European Journal of Pharmacology. 893. 173810–173810. 25 indexed citations
6.
Zheng, Zhe, et al.. (2019). Long-term efficacy of ventriculoperitoneal shunt in patient with idiopathic normal pressure hydrocephalus. Zhonghua shenjing waike zazhi. 35(2). 140–143. 1 indexed citations
7.
Yuan, Tingting, Lan Ma, Bao‐Gui Jiang, et al.. (2019). First Confirmed Infection of Candidatus Rickettsia Tarasevichiae in Rodents Collected from Northeastern China. Vector-Borne and Zoonotic Diseases. 20(2). 88–92. 10 indexed citations
8.
Liang, Weicheng, Cheuk-Wa Wong, Puping Liang, et al.. (2019). Translation of the circular RNA circβ-catenin promotes liver cancer cell growth through activation of the Wnt pathway. Genome biology. 20(1). 84–84. 369 indexed citations breakdown →
9.
Lu, Feng, Liu Shi, Yingfei Lu, et al.. (2018). Linc-ROR Promotes Osteogenic Differentiation of Mesenchymal Stem Cells by Functioning as a Competing Endogenous RNA for miR-138 and miR-145. Molecular Therapy — Nucleic Acids. 11. 345–353. 96 indexed citations
10.
Li, Haixin, Ying Huang, Xian Wu, et al.. (2018). Effects of hemocoagulase agkistrodon on the coagulation factors and its procoagulant activities. Drug Design Development and Therapy. Volume 12. 1385–1398. 14 indexed citations
11.
Lu, Yingfei, Li Zhang, Mary Miu Yee Waye, Weiming Fu, & Jinfang Zhang. (2015). MiR-218 Mediates tumorigenesis and metastasis: Perspectives and implications. Experimental Cell Research. 334(1). 173–182. 56 indexed citations
12.
Zhang, Zhilun, Zhigang Gao, Ying Zhang, et al.. (2014). Effectiveness of 10-year vaccination (2001–2010) for Hepatitis A in Tianjin, China. Human Vaccines & Immunotherapeutics. 10(4). 1008–1012. 9 indexed citations
13.
Fu, Weiming, et al.. (2014). Identification of differential splicing genes in gliomas using exon expression profiling. Molecular Medicine Reports. 11(2). 843–850. 16 indexed citations
14.
Zhang, Jinfang, Weiming Fu, Ming‐Liang He, et al.. (2011). MiRNA-20a promotes osteogenic differentiation of human mesenchymal stem cells by co-regulating BMP signaling. RNA Biology. 8(5). 829–838. 224 indexed citations
15.
Lu, Chengbiao, Yue Wang, Katsutoshi Furukawa, et al.. (2006). Evidence that caspase‐1 is a negative regulator of AMPA receptor‐mediated long‐term potentiation at hippocampal synapses. Journal of Neurochemistry. 97(4). 1104–1110. 43 indexed citations
16.
17.
Fu, Weiming. (2002). Seizures and Tissue Injury Induce Telomerase in Hippocampal Microglial Cells. Experimental Neurology. 178(2). 294–300. 19 indexed citations
19.
Zhu, Haiyan, Weiming Fu, & Mark P. Mattson. (2000). The Catalytic Subunit of Telomerase Protects Neurons Against Amyloid β‐Peptide‐Induced Apoptosis. Journal of Neurochemistry. 75(1). 117–124. 142 indexed citations
20.
Guo, Qing, Weiming Fu, Frederick W. Holtsberg, Sheldon M. Steiner, & Mark P. Mattson. (1999). Superoxide mediates the cell-death-enhancing action of presenilin-1 mutations. Journal of Neuroscience Research. 56(5). 457–470. 58 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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