Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Yonghu Liang"'
Autor:
Miao Cai, Yonghu Liang, Minghui Yun, Xuan-You Chen, Haidong Yan, Zhaozhe Yu, Daoguo Yang, Guoqi Zhang
Publikováno v:
IEEE Access, Vol 7, Pp 27106-27114 (2019)
A novel silicone rubber elastic key (SREK) is proposed in this paper for surface mounting technology (SMT) applications. Effects of thermal reflowing stress on the mechanical properties of SMT-SREKs are investigated. The manufactured SMT-SREKs, which
Externí odkaz:
https://doaj.org/article/d1e5a683bdbb4cb89d11bb6e0283ad83
Autor:
Peng Guo, Bo Zhu, Hong Niu, Zezhao Wang, Yonghu Liang, Yan Chen, Lupei Zhang, Hemin Ni, Yong Guo, El Hamidi A. Hay, Xue Gao, Huijiang Gao, Xiaolin Wu, Lingyang Xu, Junya Li
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-11 (2018)
Abstract Background Running multiple-chain Markov Chain Monte Carlo (MCMC) provides an efficient parallel computing method for complex Bayesian models, although the efficiency of the approach critically depends on the length of the non-parallelizable
Externí odkaz:
https://doaj.org/article/71f0e35c93f449e68ac85c3b6edba0da
Autor:
Bo Zhu, Hong Niu, Wengang Zhang, Zezhao Wang, Yonghu Liang, Long Guan, Peng Guo, Yan Chen, Lupei Zhang, Yong Guo, Heming Ni, Xue Gao, Huijiang Gao, Lingyang Xu, Junya Li
Publikováno v:
BMC Genomics, Vol 18, Iss 1, Pp 1-15 (2017)
Abstract Background Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle
Externí odkaz:
https://doaj.org/article/1b62b6ff57e2486b939ba1ed7c3b4061
Autor:
Peng Guo, Bo Zhu, Lingyang Xu, Hong Niu, Zezhao Wang, Long Guan, Yonghu Liang, Hemin Ni, Yong Guo, Yan Chen, Lupei Zhang, Xue Gao, Huijiang Gao, Junya Li
Publikováno v:
PLoS ONE, Vol 12, Iss 7, p e0179885 (2017)
Genomic selection has been widely used for complex quantitative trait in farm animals. Estimations of breeding values for slaughter traits are most important to beef cattle industry, and it is worthwhile to investigate prediction accuracies of genomi
Externí odkaz:
https://doaj.org/article/42fac1553bce47dd81a9b716b1dbe144
Autor:
Zezhao Wang, De-jiang Zhu, Xiao-cheng Xu, Hong Niu, Li JunYa, Yan-zi Tian, Binghai Cao, Xiong Xiong, Hong-xue Shen, Yan Chen, Xu Ling, Yonghu Liang, Bo Zhu, Wen-gang Zhang, Ai-zhen Guo
Publikováno v:
Journal of Integrative Agriculture, Vol 16, Iss 10, Pp 2246-2256 (2017)
Traditionally, Chinese indigenous cattle is geographically widespread. The present study analyzed based on genome-wide variants to evaluate the genetic background among 157 individuals from four representative indigenous cattle breeds of Hubei Provin
Autor:
Lingyang Xu, Xiao-Lin Wu, Peng Guo, El Hamidi A. Hay, Bo Zhu, Hemin Ni, Xue Gao, Yong Guo, Yonghu Liang, Huijiang Gao, Lupei Zhang, Zezhao Wang, Junya Li, Hong Niu, Yan Chen
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-11 (2018)
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-11 (2018)
Background Running multiple-chain Markov Chain Monte Carlo (MCMC) provides an efficient parallel computing method for complex Bayesian models, although the efficiency of the approach critically depends on the length of the non-parallelizable burn-in
Autor:
Huijiang Gao, Wengang Zhang, Long Guan, Lingyang Xu, Zezhao Wang, Bo Zhu, Heming Ni, Peng Guo, Junya Li, Hong Niu, Yan Chen, Xue Gao, Yonghu Liang, Lupei Zhang, Yong Guo
Publikováno v:
BMC Genomics
BMC Genomics, Vol 18, Iss 1, Pp 1-15 (2017)
BMC Genomics, Vol 18, Iss 1, Pp 1-15 (2017)
Background Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this
Autor:
Zhu, Bo, Niu, Hong, Wengang Zhang, Zezhao Wang, Yonghu Liang, Guan, Long, Guo, Peng, Chen, Yan, Lupei Zhang, Guo, Yong, Heming Ni, Gao, Xue, Huijiang Gao, Lingyang Xu, Li, Junya
Estimates of phenotypic correlations (upper diagonals) and genetic correlation (lower diagonals) between 21 phenotypes in Chinese Simmental beef cattle. (DOCX 19Â kb)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::201d2a757bc19d427a08e9468c05f8b2