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Position: Home > Articles > Bayesian Statistics in Genetics Chinese Agricultural Science Bulletin 2010,26 (20) 122-124

贝叶斯统计学在遗传中的应用

作  者:
王伟;李玉莲;崔秀珍;黄中文
单  位:
河南科技学院生命科技学院;山东农业科学院作物研究所
关键词:
贝叶斯统计;先验信息;后验信息
摘  要:
经典统计分析方法在遗传学中已经得到广泛应用,而在解决许多复杂的遗传学问题中,贝叶斯方法可能显得更为有效。贝叶斯方法的优势是可以有效利用先验信息,提供解决问题更为直接的方法,从而更加直观地解释试验结果。由于从基因组及基因表达中获得的信息量越来越多,因此对统计分析方法的需求也随之增大。贝叶斯统计方法扩大了统计学研究的领域,其应用也逐渐受到重视。
译  名:
Bayesian Statistics in Genetics
作  者:
Wang Wei1,Li Yulian2,Cui Xiuzhen1,Huang Zhongwen1 (1Life Science and Technology College,Henan Institute of Science and Technology,Xinxiang Henan 453003; 2Crop Sciences Institute,Shandong Academy of Agricultural Science,Jinan Shandong 250100)
关键词:
Bayesian statistics; prior information; post information
摘  要:
Statistical analyses have been used in many fields of genetic research. But in the utility of a Bayesian statistics for complex problems,geneticists are finding this framework useful and are increasingly utilizing the power of this approach. Incorporation of prior information and addressing the question directly are advantages of Bayesian statistical methods,then we get more intuitive explanation of experiment results. As more information becomes available from genome and gene-expression projects,the demand for methods of analysis increases. Expanding the area of statistics,Bayesian methods are made more importance gradually.

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