Ming Cang
Impact in
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- Animal Genetics and Reproduction
- Genetic and phenotypic traits in livestock
Papers in
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- CRISPR and Genetic Engineering 6
- Muscle Physiology and Disorders 5
- RNA Research and Splicing 3
- Molecular Biology Techniques and Applications 2
- Genetics 11
- Animal Genetics and Reproduction 9
- Genetic and phenotypic traits in livestock 2
- Co-authors
- Hao Liang (9 shared papers)Kehua Zhang (1 shared paper)Yang Li (1 shared paper)Dongjun Liu (7 shared papers)Ju Zhang (5 shared papers)Jianlong Yuan (4 shared papers)Xudong Guo (2 shared papers)Haiqing Wu (3 shared papers)
- Journals
- Cell Biology International (2 papers)International Journal of Biological Sciences (2 papers)Animals (2 papers)Journal of Cellular Biochemistry (1 paper)FEBS Journal (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Ming Cang
21 papers receiving 313 citations
Peers
Comparison fields: 5 of 55
- Genetics 147
- Business and International Management 10
- Urology 31
- Aging 6
- Molecular Biology 234
Countries citing papers authored by Ming Cang
This map shows the geographic impact of Ming Cang'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 Ming Cang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Cang more than expected).
Fields of papers citing papers by Ming Cang
This network shows the impact of papers produced by Ming Cang. 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 Ming Cang. The network helps show where Ming Cang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Cang, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 83 | |
| 2 | 2012 | 37 | |
| 3 | 2018 | 34 | |
| 4 | 2019 | 31 | |
| 5 | 2019 | 26 | |
| 6 | 2021 | 22 | |
| 7 | 2019 | 19 | |
| 8 | 2016 | 11 | |
| 9 | 2023 | 10 | |
| 10 | 2020 | 8 | |
| 11 | 2011 | 8 | |
| 12 | 2019 | 5 | |
| 13 | 2010 | 5 | |
| 14 | 2018 | 4 | |
| 15 | 2011 | 4 | |
| 16 | 2015 | 4 | |
| 17 | 2015 | 3 | |
| 18 | 2025 | 2 | |
| 19 | The Study on the Gene Expression of Preimplantation IVF Bovine Embryos | 2010 | 2 |
| 20 | 2025 | 1 |
About Ming Cang
Ming Cang is a scholar working on Molecular Biology, Genetics, Public Health, Environmental and Occupational Health, Surgery and Urology, having authored 21 papers that have together received 320 indexed citations. Recurring topics across this work include Animal Genetics and Reproduction (9 papers), CRISPR and Genetic Engineering (6 papers), Muscle Physiology and Disorders (5 papers), RNA Research and Splicing (3 papers), Reproductive Biology and Fertility (3 papers), Genetic and phenotypic traits in livestock (2 papers), Hair Growth and Disorders (2 papers) and Molecular Biology Techniques and Applications (2 papers). The work is most often cited by research in Genetics (147 citations), Business and International Management (10 citations), Urology (31 citations), Aging (6 citations) and Molecular Biology (234 citations). Ming Cang has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Hao Liang, Kehua Zhang, Yang Li, Dongjun Liu, Ju Zhang, Jianlong Yuan, Xudong Guo, Haiqing Wu, Fei Hao and Xiao Hu. Their work appears in journals such as Cell Biology International, International Journal of Biological Sciences, Animals, Journal of Cellular Biochemistry and FEBS Journal.
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.