Kun Mu

3.2k citations
60 papers · 1.6k · h-index 24

Impact in

    • Cancer-related molecular mechanisms research
  • Oncology top 10%
    • Cancer-related Molecular Pathways

Papers in

    • Ubiquitin and proteasome pathways 4
    • Inflammasome and immune disorders 4
    • Circular RNAs in diseases 4
    • DNA Repair Mechanisms 3
    • Cancer-related Molecular Pathways 6

Kun Mu

58 papers receiving 1.6k citations

Peers

Kun Mu
Comparison fields: 5 of 111
  • Cancer Research 251
  • Oncology 343
  • Immunology 267
  • Molecular Biology 873
  • Pathology and Forensic Medicine 174
Replace Johanna Louhimo with:
Johanna Louhimo Finland
Yixin Tan China
Liyun Xu China
Liming Yu China
Jinbiao Chen Australia
Chenghai Zhao China
Fan Lin United States
Ki Cheol Park South Korea
Junji Yamashita Japan
Reju Korah United States
Kun Mu relative to Johanna Louhimo Finland Johanna Louhimo's profile →
Citations per field
00.5×2×3.2×
Johanna Louhimo · 1×
Citations per year

Countries citing papers authored by Kun Mu

Since Specialization
Citations

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

Fields of papers citing papers by Kun Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013245
2 2015121
3 2016100
4 202099
5 201976
6 201372
7 201457
8 201857
9 202253
10 201349
11 201141
12 201737
13 201537
14 200936
15 202036
16 201233
17 201832
18 200932
19 202032
20 201729

About Kun Mu

Kun Mu is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Genetics, having authored 60 papers that have together received 1.6k indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (6 papers), Cancer-related Molecular Pathways (6 papers), Breast Cancer Treatment Studies (5 papers), Ubiquitin and proteasome pathways (4 papers), Pregnancy-related medical research (4 papers), Inflammasome and immune disorders (4 papers), Circular RNAs in diseases (4 papers) and DNA Repair Mechanisms (3 papers). The work is most often cited by research in Cancer Research (251 citations), Oncology (343 citations), Immunology (267 citations), Molecular Biology (873 citations) and Pathology and Forensic Medicine (174 citations). Kun Mu has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Wei Zhao, Lihui Han, Tao Li, Pengbo Guo, Wanwan Huai, Qing Wei, Ying Zhang, Zhaowen Yang, Xiaoqing Jia and Xiaomin Ma. Their work appears in journals such as Oncotarget, Diagnostic Pathology, Cell Death and Disease, Scientific Reports and Frontiers in Genetics.

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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