Jun Wan

5.1k citations
166 papers · 3.9k · h-index 35

Impact in

Papers in

    • Circular RNAs in diseases 21
    • RNA Research and Splicing 10
    • RNA modifications and cancer 8
    • MicroRNA in disease regulation 25
    • Cancer-related molecular mechanisms research 18
    • Cancer, Hypoxia, and Metabolism 8

Jun Wan

161 papers receiving 3.9k citations

Peers

Jun Wan
Comparison fields: 5 of 126
  • Cancer Research 1.2k
  • Immunology 669
  • Neurology 222
  • Molecular Biology 1.8k
  • Biological Psychiatry 58
Replace Bernd Baumann with:
Bernd Baumann Germany
Robert C. Axtell United States
Mirko H. H. Schmidt Germany
David Otaegui Spain
Hao Xue China
Pengxu Qian China
Tiziana Annese Italy
Jianning Zhang China
Sergio Caballero United States
Jun Wan relative to Bernd Baumann Germany Bernd Baumann's profile →
Citations per field
00.5×1.5×2×
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 166 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014278
2 2010194
3 2020130
4 2010114
5 2020111
6 2013104
7 201996
8 201290
9 201377
10 201676
11 201170
12 202067
13 200367
14 201762
15 200061
16 201360
17 201760
18 201959
19 201459
20 201852

About Jun Wan

Jun Wan is a scholar working on Molecular Biology, Cancer Research, Immunology, Surgery and Genetics, having authored 166 papers that have together received 3.9k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (25 papers), Circular RNAs in diseases (21 papers), Cancer-related molecular mechanisms research (18 papers), RNA Research and Splicing (10 papers), Genomic variations and chromosomal abnormalities (10 papers), RNA modifications and cancer (8 papers), Cancer, Hypoxia, and Metabolism (8 papers) and Immune Response and Inflammation (7 papers). The work is most often cited by research in Cancer Research (1.2k citations), Immunology (669 citations), Neurology (222 citations), Molecular Biology (1.8k citations) and Biological Psychiatry (58 citations). Jun Wan has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Bo Yu, Jie Pan, Nana Ma, Wei Wu, Ming Guan, Xiaoyang Ye, Kepeng Wang, Yifei Cai, Zhenguo Wu and Wei Zhang. Their work appears in journals such as Frontiers in Molecular Neuroscience, Structure, Journal of Experimental & Clinical Cancer Research, Medical Oncology and PLoS ONE.

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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