Dan Ge
Impact in
- Developmental Neuroscience top 5%
- Biomaterials top 5%
- Electrospun Nanofibers in Biomedical Applications
Papers in
-
- Bacterial biofilms and quorum sensing 6
- Pluripotent Stem Cells Research 5
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- 3D Printing in Biomedical Research 7
- Bone Tissue Engineering Materials 5
- Co-authors
- Xuehu Ma (15 shared papers)Shui Guan (13 shared papers)Tianqing Liu (13 shared papers)Tianqing Liu (9 shared papers)Xiangqin Li (13 shared papers)Kedong Song (11 shared papers)Wenfang Li (4 shared papers)Jianqiang Xu (4 shared papers)
- Journals
- Applied Biochemistry and Biotechnology (2 papers)International Journal of Nanomedicine (2 papers)Biomaterials Science (2 papers)Scientific Reports (2 papers)ACS Biomaterials Science & Engineering (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Dan Ge
55 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 129
- Developmental Neuroscience 77
- Biomaterials 253
- Cellular and Molecular Neuroscience 234
- Molecular Medicine 63
- Biomedical Engineering 562
Countries citing papers authored by Dan Ge
This map shows the geographic impact of Dan Ge'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 Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Ge more than expected).
Fields of papers citing papers by Dan Ge
This network shows the impact of papers produced by Dan Ge. 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 Ge. The network helps show where Dan Ge may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Ge, 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 | 2017 | 129 | |
| 2 | 2018 | 108 | |
| 3 | 2006 | 104 | |
| 4 | 2017 | 87 | |
| 5 | 2008 | 79 | |
| 6 | 2016 | 61 | |
| 7 | 2013 | 56 | |
| 8 | 2019 | 56 | |
| 9 | 2019 | 48 | |
| 10 | 2019 | 43 | |
| 11 | 2020 | 39 | |
| 12 | 2022 | 38 | |
| 13 | 2019 | 37 | |
| 14 | 2012 | 34 | |
| 15 | 2009 | 34 | |
| 16 | 2021 | 33 | |
| 17 | 2023 | 32 | |
| 18 | 2013 | 31 | |
| 19 | 2016 | 26 | |
| 20 | 2011 | 21 |
About Dan Ge
Dan Ge is a scholar working on Molecular Biology, Biomedical Engineering, Cellular and Molecular Neuroscience, Developmental Neuroscience and Surgery, having authored 59 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neurogenesis and neuroplasticity mechanisms (7 papers), 3D Printing in Biomedical Research (7 papers), Bacterial biofilms and quorum sensing (6 papers), Neuroscience and Neural Engineering (5 papers), Nerve injury and regeneration (5 papers), Bone Tissue Engineering Materials (5 papers), Pluripotent Stem Cells Research (5 papers) and Tissue Engineering and Regenerative Medicine (5 papers). The work is most often cited by research in Developmental Neuroscience (77 citations), Biomaterials (253 citations), Cellular and Molecular Neuroscience (234 citations), Molecular Medicine (63 citations) and Biomedical Engineering (562 citations). Dan Ge has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Xuehu Ma, Shui Guan, Tianqing Liu, Tianqing Liu, Xiangqin Li, Kedong Song, Wenfang Li, Jianqiang Xu, Shuping Wang and Changkai Sun. Their work appears in journals such as Applied Biochemistry and Biotechnology, International Journal of Nanomedicine, Biomaterials Science, Scientific Reports and ACS Biomaterials Science & Engineering.
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.