Jun Fu

1.3k citations
61 papers · 839 indexed · h-index 18

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Circular RNAs in diseases
    • RNA modifications and cancer
    • RNA Research and Splicing

Papers in

Jun Fu

57 papers receiving 826 citations

Peers

Jun Fu
Comparison fields: 5 of 90
  • Cancer Research 248
  • Molecular Biology 392
  • Immunology 108
  • Cell Biology 60
  • Epidemiology 119
Replace Maya R. Vilà with:
Maya R. Vilà Spain
Prathibha Ranganathan India
Tao Wan China
Yi‐Ying Wu Taiwan
Xue Liu China
Zhihua Tao China
David Brodin Sweden
Rebecca E. McIntyre United Kingdom
Y. Otsuki Japan
Rika Ouchida Japan
Jun Fu relative to Maya R. Vilà Spain Maya R. Vilà's profile →
Citations per field
00.5×5.9×
Maya R. Vilà · 1×
Citations per year

Countries citing papers authored by Jun Fu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201475
2
LncRNA-LINC00152 down-regulated by miR-376c-3p restricts viability and promotes apoptosis of colorectal cancer cells.
201661
3 202245
4 201943
5 201337
6 201835
7 201931
8 202130
9 201829
10 201128
11 201326
12 202026
13 200226
14 202025
15 202025
16 201022
17 201621
18 201220
19 201817
20 201916

About Jun Fu

Jun Fu is a scholar working on Cancer Research, Biological Psychiatry, Toxicology, Immunology and Molecular Biology, having authored 61 papers that have together received 839 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (6 papers), Circular RNAs in diseases (5 papers), RNA modifications and cancer (5 papers), MicroRNA in disease regulation (5 papers), Cancer-related gene regulation (4 papers), Kruppel-like factors research (3 papers), Biochemical Analysis and Sensing Techniques (3 papers) and Immunotherapy and Immune Responses (3 papers). The work is most often cited by research in Cancer Research (248 citations), Molecular Biology (392 citations), Immunology (108 citations), Cell Biology (60 citations) and Epidemiology (119 citations). Jun Fu has collaborated with scholars based in China, United States and Tunisia. Frequent co-authors include Zhijin Zhang, Yuhao Zhang, Xianju Qin, Shengli Pan, Yingying Deng, Yue Feng, Cuicui Ge, Yuhao Zhang, Yuexia Wang and Benling Qi. Their work appears in journals such as OncoTargets and Therapy, Cellular Physiology and Biochemistry, Marine Drugs, Cell Death and Disease and International Journal of Molecular Medicine.

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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