Ming‐Yuan Xue
- Agronomy and Crop Science top 0.5%
- Molecular Biology
- Genetics top 10%
- Food Science top 10%
- Ecology, Evolution, Behavior and Systematics top 10%
- Topics
- Ruminant Nutrition and Digestive Physiology (18 papers)Gut microbiota and health (12 papers)Genetic and phenotypic traits in livestock (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaApplied and Environmental MicrobiologyCarbohydrate Polymers
- Partner nations
- ChinaCanadaNew Zealand
In The Last Decade
Ming‐Yuan Xue
32 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Agronomy and Crop Science 784
- Molecular Biology 484
- Genetics 242
- Food Science 141
- Ecology, Evolution, Behavior and Systematics 123
Countries citing papers authored by Ming‐Yuan Xue
This map shows the geographic impact of Ming‐Yuan Xue'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‐Yuan Xue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming‐Yuan Xue more than expected).
Fields of papers citing papers by Ming‐Yuan Xue
This network shows the impact of papers produced by Ming‐Yuan Xue. 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‐Yuan Xue. The network helps show where Ming‐Yuan Xue may publish in the future.
Co-authorship network of co-authors of Ming‐Yuan Xue
This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Yuan Xue. A scholar is included among the top collaborators of Ming‐Yuan Xue based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming‐Yuan Xue. Ming‐Yuan Xue is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 14 | |
| 5 | 7 | |
| 6 | 32 | |
| 7 | 6 | |
| 8 | 42 | |
| 9 | Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattlebreakdown → | 104 |
| 10 | 6 | |
| 11 | 22 | |
| 12 | Multi-omics reveals that the rumen microbiome and its metabolome together with the host metabolome contribute to individualized dairy cow performancebreakdown → | 281 |
| 13 | 85 | |
| 14 | 14 | |
| 15 | 46 | |
| 16 | 81 | |
| 17 | 60 | |
| 18 | 120 | |
| 19 | 55 | |
| 20 | 1 |
About Ming‐Yuan Xue
Ming‐Yuan Xue is a scholar working on Agronomy and Crop Science, Molecular Medicine and Microbiology, having authored 33 papers that have together received 1.2k indexed citations. Recurring topics across this work include Ruminant Nutrition and Digestive Physiology (18 papers), Gut microbiota and health (12 papers) and Genetic and phenotypic traits in livestock (9 papers). The work is most often cited by research in Agronomy and Crop Science (784 citations), Animal Science and Zoology (121 citations) and Genetics (242 citations). Ming‐Yuan Xue has collaborated with scholars based in China, Canada and New Zealand. Frequent co-authors include Jianxin Liu, Hui‐Zeng Sun, Le Luo Guan, Xuehui Wu, Yifan Zhong, Yun‐Yi Xie, Xinke Wu, Xiao Xie, Jiakun Wang and Chunlei Yang. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied and Environmental Microbiology and Carbohydrate Polymers.
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.