Mingze Yao
Impact in
Papers in
-
- CRISPR and Genetic Engineering 9
- Genomics and Chromatin Dynamics 7
- Epigenetics and DNA Methylation 5
- Pluripotent Stem Cells Research 5
- RNA Research and Splicing 3
- Co-authors
- Aihua Liang (4 shared papers)Huibing Wang (3 shared papers)Xianping Fu (3 shared papers)Hongjie Yao (9 shared papers)Mei-Bian Hu (1 shared paper)Guangqi Jiang (1 shared paper)Zetian Mi (1 shared paper)Kaimeng Huang (4 shared papers)
- Journals
- Stem Cell Research (3 papers)Nature Communications (2 papers)International Journal of Molecular Sciences (2 papers)Cell stem cell (2 papers)Stem Cell Research & Therapy (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Mingze Yao
32 papers receiving 707 citations
Mingze Yao's Hit Papers
Peers
Comparison fields: 5 of 106
- Computational Mathematics 8
- Computer Vision and Pattern Recognition 135
- Aging 11
- Molecular Biology 414
- Developmental Neuroscience 18
Countries citing papers authored by Mingze Yao
This map shows the geographic impact of Mingze Yao'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 Mingze Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingze Yao more than expected).
Fields of papers citing papers by Mingze Yao
This network shows the impact of papers produced by Mingze Yao. 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 Mingze Yao. The network helps show where Mingze Yao may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingze Yao, 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 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 95 | |
| 2 | Manifold-Based Incomplete Multi-View Clustering via Bi-Consistency Guidance Hit paper breakdown → | 2024 | 74 |
| 3 | 2017 | 72 | |
| 4 | 2023 | 70 | |
| 5 | 2018 | 53 | |
| 6 | 2013 | 46 | |
| 7 | 2017 | 43 | |
| 8 | 2013 | 39 | |
| 9 | 2021 | 30 | |
| 10 | 2015 | 19 | |
| 11 | 2022 | 18 | |
| 12 | 2018 | 17 | |
| 13 | 2023 | 14 | |
| 14 | 2020 | 12 | |
| 15 | 2013 | 12 | |
| 16 | 2020 | 11 | |
| 17 | 2020 | 10 | |
| 18 | 2020 | 9 | |
| 19 | 2021 | 9 | |
| 20 | 2024 | 8 |
About Mingze Yao
Mingze Yao is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Rheumatology, Plant Science and Oncology, having authored 34 papers that have together received 714 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (9 papers), Genomics and Chromatin Dynamics (7 papers), Epigenetics and DNA Methylation (5 papers), Pluripotent Stem Cells Research (5 papers), Phytase and its Applications (4 papers), Folate and B Vitamins Research (4 papers), RNA Research and Splicing (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Computational Mathematics (8 citations), Computer Vision and Pattern Recognition (135 citations), Aging (11 citations), Molecular Biology (414 citations) and Developmental Neuroscience (18 citations). Mingze Yao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Aihua Liang, Huibing Wang, Xianping Fu, Hongjie Yao, Mei-Bian Hu, Guangqi Jiang, Zetian Mi, Kaimeng Huang, Yuejun Fu and Wei Wang. Their work appears in journals such as Stem Cell Research, Nature Communications, International Journal of Molecular Sciences, Cell stem cell and Stem Cell Research & Therapy.
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.