Dian Fu

906 citations
22 papers · 648 · h-index 12

Impact in

    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research
    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation

Papers in

    • Genomics, phytochemicals, and oxidative stress 2
    • Epigenetics and DNA Methylation 2
    • Bladder and Urothelial Cancer Treatments 4

Dian Fu

21 papers receiving 630 citations

Peers

Dian Fu
Comparison fields: 5 of 84
  • Infectious Diseases 244
  • Cancer Research 102
  • Obstetrics and Gynecology 45
  • Neurology 85
  • Oncology 83
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Xiangqiong Liu China
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Citations per field
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Citations per year

Countries citing papers authored by Dian Fu

Since Specialization
Citations

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

Fields of papers citing papers by Dian Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020282
2 201867
3 202238
4 201735
5 202033
6 201433
7 202030
8 201427
9 201717
10 202016
11 202215
12
Long non-coding RNA PlncRNA-1 regulates cell proliferation, apoptosis, and autophagy in septic acute kidney injury by regulating BCL2.
201813
13 202011
14 20208
15 20188
16 20247
17 20244
18 20251
19 20231
20
[Efficacy of Lamiophlomis Rotata Capsule in the treatment of type ⅢB prostatitis].
20171

About Dian Fu

Dian Fu is a scholar working on Molecular Biology, Surgery, Neurology, Cancer Research and Infectious Diseases, having authored 22 papers that have together received 648 indexed citations. Recurring topics across this work include Bladder and Urothelial Cancer Treatments (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 Clinical Research Studies (3 papers), Long-Term Effects of COVID-19 (3 papers), Cancer-related molecular mechanisms research (3 papers), Genomics, phytochemicals, and oxidative stress (2 papers), Cancer Immunotherapy and Biomarkers (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Infectious Diseases (244 citations), Cancer Research (102 citations), Obstetrics and Gynecology (45 citations), Neurology (85 citations) and Oncology (83 citations). Dian Fu has collaborated with scholars based in China. Frequent co-authors include Faxiang Wang, Xinyi Xia, Dong Wang, Fang Zhang, Mingxiang Ye, Tangfeng Lv, Yi Ren, Wen Cheng, Zhengyu Zhang and Feng Xu. Their work appears in journals such as Cellular and Molecular Biology, Toxicology and Applied Pharmacology, Oncotarget, Frontiers in Oncology and Aging.

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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