Jun Wan

5.0k citations
167 papers · 3.8k indexed · h-index 34

Impact in

Papers in

    • MicroRNA in disease regulation 28
    • Cancer-related molecular mechanisms research 21
    • Cancer, Hypoxia, and Metabolism 9

Jun Wan

161 papers receiving 3.7k citations

Peers

Jun Wan
Comparison fields: 5 of 128
  • Cancer Research 1.4k
  • Immunology 717
  • Molecular Biology 2.1k
  • Neurology 240
  • Biological Psychiatry 71
Replace Bernd Baumann with:
Bernd Baumann Germany
Robert C. Axtell United States
Mirko H. H. Schmidt Germany
David Otaegui Spain
Sergio Caballero United States
Pengxu Qian China
Wen Yue China
Yvonne Reiss Germany
Min Zheng China
Jun Wan relative to Bernd Baumann Germany Bernd Baumann's profile →
Citations per field
00.5×1.5×2.1×
Bernd Baumann · 1×
Citations per year

Countries citing papers authored by Jun Wan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 167 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014263
2 2010186
3 2020125
4 2010112
5 2020110
6 2013101
7 201992
8 201287
9 201375
10 201674
11 201168
12 200366
13 202062
14 201760
15 201360
16 201760
17 200058
18 201457
19 201955
20 200851

About Jun Wan

Jun Wan is a scholar working on Cancer Research, Immunology, Molecular Biology, Rheumatology and Pathology and Forensic Medicine, having authored 167 papers that have together received 3.8k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (28 papers), Circular RNAs in diseases (22 papers), Cancer-related molecular mechanisms research (21 papers), RNA Research and Splicing (12 papers), RNA modifications and cancer (11 papers), Genomic variations and chromosomal abnormalities (11 papers), Cancer, Hypoxia, and Metabolism (9 papers) and Cancer-related gene regulation (8 papers). The work is most often cited by research in Cancer Research (1.4k citations), Immunology (717 citations), Molecular Biology (2.1k citations), Neurology (240 citations) and Biological Psychiatry (71 citations). Jun Wan has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Bo Yu, Nana Ma, Jie Pan, Wei Wu, Ming Guan, Xiaoyang Ye, Kepeng Wang, Yifei Cai, Zhenguo Wu and Yun Che. Their work appears in journals such as Structure, Frontiers in Molecular Neuroscience, Journal of Biological Chemistry, Medical Oncology and Journal of Experimental & Clinical Cancer Research.

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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