Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model-Reference-Cited by-同舟云学术

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Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model

Published:2015-10-14 Issue:1 Volume:16 Page:
ISSN:1471-2156
Container-title:BMC Genetics
language:en
Short-container-title:BMC Genet

Author:

Gao Ning,Li Jiaqi,He Jinlong,Xiao Guang,Luo Yuanyu,Zhang Hao,Chen Zanmou,Zhang Zhe

Funder

National Natural Science Foundation of China

China Agriculture Research System

Guangdong Natural Science Foundation

Key Scientific and Technological Projects of Guangzhou

Publisher

Springer Science and Business Media LLC

Subject

Genetics(clinical),Genetics

Link

http://link.springer.com/content/pdf/10.1186/s12863-015-0278-9

Reference58 articles.

1. Vachon CM, van Gils CH, Sellers TA, Ghosh K, Pruthi S, Brandt KR, et al. Mammographic density, breast cancer risk and risk prediction. Breast Cancer Res. 2007, 9(6):doi: 10.1186/bcr1829 .

2. Jostins L, Barrett JC. Genetic risk prediction in complex disease. Hum Mol Genet. 2011;20:R182–8.

3. Domchek SM, Eisen A, Calzone K, Stopfer J, Blackwood A, Weber BL. Application of breast cancer risk prediction models in clinical practice. J Clin Oncol. 2003;21(4):593–601.

4. Bonassi S, Au WW. Biomarkers in molecular epidemiology studies for health risk prediction. Mutat Res Rev Mutat Res. 2002;511(1):73–86.

5. Bouquet A, Juga J. Integrating genomic selection into dairy cattle breeding programmes: a review. Animal. 2013;7(5):705–13.

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