Kun Mu
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- Oncology top 10%
- Cancer-related Molecular Pathways
Papers in
-
- Circular RNAs in diseases 5
- DNA Repair Mechanisms 4
- Oncology 18
- Cancer-related Molecular Pathways 6
- Co-authors
- Lihui Han (4 shared papers)Wei Zhao (4 shared papers)Pengbo Guo (3 shared papers)Tao Li (3 shared papers)Wanwan Huai (3 shared papers)Qing Wei (3 shared papers)Ying Zhang (2 shared papers)Zhaowen Yang (2 shared papers)
- Journals
- Oncotarget (5 papers)Diagnostic Pathology (3 papers)Cell Death and Disease (3 papers)Scientific Reports (2 papers)Laboratory Investigation (2 papers)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Kun Mu
57 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 113
- Cancer Research 310
- Oncology 419
- Immunology 293
- Molecular Biology 949
- Nephrology 77
Countries citing papers authored by Kun Mu
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
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.
All Works
Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 232 | |
| 2 | 2015 | 116 | |
| 3 | 2016 | 97 | |
| 4 | 2020 | 95 | |
| 5 | 2019 | 74 | |
| 6 | 2013 | 71 | |
| 7 | 2014 | 57 | |
| 8 | 2018 | 57 | |
| 9 | 2022 | 51 | |
| 10 | 2013 | 49 | |
| 11 | 2011 | 39 | |
| 12 | 2017 | 37 | |
| 13 | 2009 | 36 | |
| 14 | 2020 | 35 | |
| 15 | 2015 | 35 | |
| 16 | 2012 | 33 | |
| 17 | 2018 | 32 | |
| 18 | 2009 | 31 | |
| 19 | 2020 | 30 | |
| 20 | 2017 | 29 |
About Kun Mu
Kun Mu is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 59 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (6 papers), Spine and Intervertebral Disc Pathology (6 papers), Circular RNAs in diseases (5 papers), Breast Cancer Treatment Studies (5 papers), Pregnancy-related medical research (5 papers), Cancer Genomics and Diagnostics (4 papers), Musculoskeletal pain and rehabilitation (4 papers) and DNA Repair Mechanisms (4 papers). The work is most often cited by research in Cancer Research (310 citations), Oncology (419 citations), Immunology (293 citations), Molecular Biology (949 citations) and Nephrology (77 citations). Kun Mu has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Lihui Han, Wei Zhao, Pengbo Guo, Tao Li, 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 Laboratory Investigation.
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.