Dan Mu
Impact in
- Molecular Medicine top 10%
- Modeling and Simulation top 5%
Papers in
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- Extracellular vesicles in disease 6
-
- Nanoplatforms for cancer theranostics 11
- Advanced X-ray and CT Imaging 6
- Biosensors and Analytical Detection 6
- Co-authors
- Hua Xiang (6 shared papers)Dacheng Wang (6 shared papers)Tiedong Wang (6 shared papers)Changjin Xu (2 shared papers)Haisi Dong (2 shared papers)Bangbang Li (3 shared papers)Di Ming (3 shared papers)Xiaobo Zhong (3 shared papers)
- Journals
- Nature Communications (4 papers)ACS Nano (3 papers)ACS Applied Materials & Interfaces (3 papers)Frontiers in Immunology (2 papers)Advanced Healthcare Materials (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Dan Mu
92 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 140
- Molecular Medicine 59
- Modeling and Simulation 48
- Biomaterials 136
- Microbiology 63
- Endocrinology 52
Countries citing papers authored by Dan Mu
This map shows the geographic impact of Dan 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 Dan Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Mu more than expected).
Fields of papers citing papers by Dan Mu
This network shows the impact of papers produced by Dan 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 Dan Mu. The network helps show where Dan Mu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan 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 100 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 122 | |
| 2 | 2017 | 92 | |
| 3 | 2018 | 65 | |
| 4 | 2021 | 60 | |
| 5 | 2022 | 55 | |
| 6 | 2023 | 53 | |
| 7 | 2011 | 50 | |
| 8 | 2022 | 49 | |
| 9 | 2021 | 48 | |
| 10 | 2020 | 47 | |
| 11 | 2020 | 46 | |
| 12 | 2021 | 40 | |
| 13 | 2022 | 38 | |
| 14 | 2016 | 34 | |
| 15 | 2022 | 33 | |
| 16 | 2020 | 32 | |
| 17 | 2022 | 32 | |
| 18 | 2020 | 30 | |
| 19 | 2020 | 29 | |
| 20 | 2018 | 28 |
About Dan Mu
Dan Mu is a scholar working on Molecular Biology, Biomedical Engineering, Immunology, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging, having authored 100 papers that have together received 1.6k indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (11 papers), Cardiac Imaging and Diagnostics (9 papers), Topological Materials and Phenomena (7 papers), Advanced X-ray and CT Imaging (6 papers), Biosensors and Analytical Detection (6 papers), Extracellular vesicles in disease (6 papers), HIV Research and Treatment (5 papers) and Cardiovascular Function and Risk Factors (5 papers). The work is most often cited by research in Molecular Medicine (59 citations), Modeling and Simulation (48 citations), Biomaterials (136 citations), Microbiology (63 citations) and Endocrinology (52 citations). Dan Mu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Hua Xiang, Dacheng Wang, Tiedong Wang, Changjin Xu, Haisi Dong, Bangbang Li, Di Ming, Xiaobo Zhong, Junjie Cao and Ling Zhong. Their work appears in journals such as Nature Communications, ACS Nano, ACS Applied Materials & Interfaces, Frontiers in Immunology and Advanced Healthcare Materials.
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.