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Lingyang Xu

Showing results (91-100 of 132) with videos related to

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Scientific Reports|August 4, 2015
Copy number variation-based genome wide association study reveals additional variants contributing to meat quality in SwineLigang Wang, Lingyang Xu, Xin Liu, et al.
Briefings in Bioinformatics|February 8, 2023
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traitsMang Liang, Sheng Cao, Tianyu Deng, et al.
Genes|December 23, 2023
Genetic Origin and Introgression Pattern of Pingliang Red Cattle Revealed Using Genome-Wide SNP AnalysesYuanqing Wang, Jun Ma, Jing Wang, et al.
Journal of Animal Science and Biotechnology|September 20, 2022
Incorporating kernelized multi-omics data improves the accuracy of genomic predictionMang Liang, Bingxing An, Tianpeng Chang, et al.
Animals : an Open Access Journal From MDPI|June 2, 2019
Genome-Wide Scan Identifies Selection Signatures in Chinese Wagyu Cattle Using a High-Density SNP ArrayZezhao Wang, Haoran Ma, Lei Xu, et al.
Foods (Basel, Switzerland)|November 14, 2023
Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef CattleJiayuan Wu, Tianyi Wu, Xueyuan Xie, et al.
Scientific Reports|June 8, 2021
Transcriptome profiling analysis of muscle tissue reveals potential candidate genes affecting water holding capacity in Chinese Simmental beef cattleLili Du, Tianpeng Chang, Bingxing An, et al.
Frontiers in Genetics|September 16, 2021
PacBio Single-Molecule Long-Read Sequencing Provides New Light on the Complexity of Full-Length Transcripts in CattleTianpeng Chang, Bingxing An, Mang Liang, et al.
Scientific Reports|July 7, 2016
Comparative analyses across cattle genders and breeds reveal the pitfalls caused by false positive and lineage-differential copy number variationsYang Zhou, Yuri T Utsunomiya, Lingyang Xu, et al.
Genomics|June 16, 2022
Integrating genomics and transcriptomics to identify candidate genes for subcutaneous fat deposition in beef cattleLili Du, Keanning Li, Tianpeng Chang, et al.
Pageof 14

Showing results (91-100 of 132) with videos related to

Sort By:
Pageof 14
Scientific Reports|August 4, 2015
Copy number variation-based genome wide association study reveals additional variants contributing to meat quality in SwineLigang Wang, Lingyang Xu, Xin Liu, et al.
Briefings in Bioinformatics|February 8, 2023
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traitsMang Liang, Sheng Cao, Tianyu Deng, et al.
Genes|December 23, 2023
Genetic Origin and Introgression Pattern of Pingliang Red Cattle Revealed Using Genome-Wide SNP AnalysesYuanqing Wang, Jun Ma, Jing Wang, et al.
Journal of Animal Science and Biotechnology|September 20, 2022
Incorporating kernelized multi-omics data improves the accuracy of genomic predictionMang Liang, Bingxing An, Tianpeng Chang, et al.
Animals : an Open Access Journal From MDPI|June 2, 2019
Genome-Wide Scan Identifies Selection Signatures in Chinese Wagyu Cattle Using a High-Density SNP ArrayZezhao Wang, Haoran Ma, Lei Xu, et al.
Foods (Basel, Switzerland)|November 14, 2023
Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef CattleJiayuan Wu, Tianyi Wu, Xueyuan Xie, et al.
Scientific Reports|June 8, 2021
Transcriptome profiling analysis of muscle tissue reveals potential candidate genes affecting water holding capacity in Chinese Simmental beef cattleLili Du, Tianpeng Chang, Bingxing An, et al.
Frontiers in Genetics|September 16, 2021
PacBio Single-Molecule Long-Read Sequencing Provides New Light on the Complexity of Full-Length Transcripts in CattleTianpeng Chang, Bingxing An, Mang Liang, et al.
Scientific Reports|July 7, 2016
Comparative analyses across cattle genders and breeds reveal the pitfalls caused by false positive and lineage-differential copy number variationsYang Zhou, Yuri T Utsunomiya, Lingyang Xu, et al.
Genomics|June 16, 2022
Integrating genomics and transcriptomics to identify candidate genes for subcutaneous fat deposition in beef cattleLili Du, Keanning Li, Tianpeng Chang, et al.
Pageof 14