Hailong Fu

1.0k total citations
21 papers, 783 citations indexed

About

Hailong Fu is a scholar working on Molecular Biology, Cancer Research and Nuclear and High Energy Physics. According to data from OpenAlex, Hailong Fu has authored 21 papers receiving a total of 783 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Cancer Research and 3 papers in Nuclear and High Energy Physics. Recurrent topics in Hailong Fu's work include MicroRNA in disease regulation (7 papers), Circular RNAs in diseases (6 papers) and Extracellular vesicles in disease (5 papers). Hailong Fu is often cited by papers focused on MicroRNA in disease regulation (7 papers), Circular RNAs in diseases (6 papers) and Extracellular vesicles in disease (5 papers). Hailong Fu collaborates with scholars based in China, Germany and Georgia. Hailong Fu's co-authors include Xu Zhang, Huan Yang, Hui Qian, Mei Wang, Wenrong Xu, Bin Zhang, Jiahui Mao, Wenrong Xu, Zixuan Sun and Yongmin Yan and has published in prestigious journals such as Scientific Reports, Stem Cells and Journal of High Energy Physics.

In The Last Decade

Hailong Fu

19 papers receiving 772 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hailong Fu China 12 584 420 92 82 80 21 783
Scott Ferguson United States 10 887 1.5× 483 1.1× 108 1.2× 50 0.6× 82 1.0× 12 1.0k
Ola A. Elgamal United States 9 662 1.1× 407 1.0× 71 0.8× 52 0.6× 44 0.6× 15 751
Giulia Chiabotto Italy 14 517 0.9× 276 0.7× 52 0.6× 22 0.3× 93 1.2× 25 696
Maria Aatonen Finland 9 850 1.5× 372 0.9× 159 1.7× 118 1.4× 78 1.0× 9 1.1k
Barbara K. Zehentner United States 17 394 0.7× 249 0.6× 40 0.4× 298 3.6× 106 1.3× 35 818
Loriana Vitillo United Kingdom 7 861 1.5× 602 1.4× 93 1.0× 145 1.8× 53 0.7× 8 988
Sini Nurmenniemi Finland 12 177 0.3× 145 0.3× 77 0.8× 185 2.3× 28 0.3× 17 459
Xiaojing Yang China 14 209 0.4× 92 0.2× 61 0.7× 167 2.0× 30 0.4× 55 594
Tomoaki Takai Japan 17 597 1.0× 455 1.1× 88 1.0× 186 2.3× 30 0.4× 37 937
Hyoun Wook Lee South Korea 16 281 0.5× 130 0.3× 53 0.6× 196 2.4× 25 0.3× 57 631

Countries citing papers authored by Hailong Fu

Since Specialization
Citations

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

Fields of papers citing papers by Hailong Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hailong Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Hailong Fu. A scholar is included among the top collaborators of Hailong 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 Hailong Fu. Hailong 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.
Meng, Lingdong, et al.. (2025). Prediction model and real-time diagnostics of hydraulic fracturing pressure for highly deviated wells in deep oil and gas reservoirs. Scientific Reports. 15(1). 3559–3559. 15 indexed citations
2.
Fu, Hailong, Yong-Hui Lin, Feng-Kun Guo, et al.. (2025). Exploring Efimov states in D*D*D* and DD*D* three-body systems. Journal of High Energy Physics. 2025(7). 1 indexed citations
3.
Huang, Min‐Wei, Hailong Fu, Toh Yen Pang, et al.. (2025). On concave polygon mesh for axisymmetric problems of solids using cell-based smoothed finite element method. Engineering Analysis with Boundary Elements. 179. 106416–106416. 1 indexed citations
4.
Fu, Hailong, et al.. (2025). Molecular Detection of Salmonella. Journal of Food Protection. 88(12). 100659–100659.
5.
Lin, Wensen, Hailong Fu, Luxin Yu, et al.. (2025). An EXPAR-CRISPR/Cas12a Assay for Rapid Detection of Salmonella. Current Microbiology. 82(6). 262–262. 2 indexed citations
6.
7.
Xia, Xin, Zhen Huang, Chengcheng Xu, et al.. (2024). Regulation of intestinal tissue‑resident memory T cells: a potential target for inflammatory bowel disease. Cell Communication and Signaling. 22(1). 610–610. 3 indexed citations
8.
Fu, Hailong, et al.. (2023). Neutron scattering off one-neutron halo nuclei in halo effective field theory. Physical review. C. 108(4). 2 indexed citations
9.
Fu, Hailong, Harald W. Grießhammer, Feng-Kun Guo, C. Hanhart, & Ulf-G. Meißner. (2022). Update on strong and radiative decays of the $$D_{s0}^*(2317)$$ and $$D_{s1}(2460)$$ and their bottom cousins. The European Physical Journal A. 58(4). 23 indexed citations
10.
Rui, Ke, Yue Hong, Qiugang Zhu, et al.. (2021). Olfactory ecto-mesenchymal stem cell-derived exosomes ameliorate murine Sjögren’s syndrome by modulating the function of myeloid-derived suppressor cells. Cellular and Molecular Immunology. 18(2). 440–451. 86 indexed citations
11.
Yang, Huan, Hailong Fu, Bo Wang, et al.. (2018). Exosomal miR‐423‐5p targets SUFU to promote cancer growth and metastasis and serves as a novel marker for gastric cancer. Molecular Carcinogenesis. 57(9). 1223–1236. 124 indexed citations
12.
Fu, Hailong, Huan Yang, Xu Zhang, et al.. (2018). Exosomal TRIM3 is a novel marker and therapy target for gastric cancer. Journal of Experimental & Clinical Cancer Research. 37(1). 162–162. 100 indexed citations
13.
Liu, L.X., Y. G., X. G. Cao, et al.. (2017). Measurements of the total cross section of Be with thermal neutrons from a photo-neutron source. Nuclear Instruments and Methods in Physics Research Section B Beam Interactions with Materials and Atoms. 410. 158–163. 4 indexed citations
14.
Fu, Hailong, Huan Yang, Xu Zhang, & Wenrong Xu. (2016). The emerging roles of exosomes in tumor–stroma interaction. Journal of Cancer Research and Clinical Oncology. 142(9). 1897–1907. 64 indexed citations
15.
16.
Zhu, Yanhua, Bin Zhang, Aihua Gong, et al.. (2016). Anti-cancer drug 3,3′-diindolylmethane activates Wnt4 signaling to enhance gastric cancer cell stemness and tumorigenesis. Oncotarget. 7(13). 16311–16324. 23 indexed citations
17.
Yang, Huan, Hailong Fu, Wenrong Xu, & Xu Zhang. (2016). Exosomal non-coding RNAs: a promising cancer biomarker. Clinical Chemistry and Laboratory Medicine (CCLM). 54(12). 1871–1879. 39 indexed citations
18.
Zhang, Bin, Yongyong Shi, Aihua Gong, et al.. (2016). HucMSC Exosome-Delivered 14-3-3ζ Orchestrates Self-Control of the Wnt Response via Modulation of YAP During Cutaneous Regeneration. Stem Cells. 34(10). 2485–2500. 134 indexed citations
19.
Zhang, Naijian, et al.. (2014). MicroRNA-100 promotes migration and invasion through mammalian target of rapamycin in esophageal squamous cell carcinoma. Oncology Reports. 32(4). 1409–1418. 21 indexed citations
20.
Yang, Shengsheng, et al.. (2013). Up-regulation of B-cell lymphoma 6 expression suppresses apoptosis of rat liver cells. Academic Journal of Second Military Medical University. 32(4). 349–354. 1 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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