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Quantitative trait loci identification for brain endophenotypes via new additive model with random networks

机译:随机网络中新添加剂模型的定量特性脑内均型鉴定

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摘要

Motivation: The identification of quantitative trait loci (QTL) is critical to the study of causal relationships between genetic variations and disease abnormalities. We focus on identifying the QTLs associated to the brain endophenotypes in imaging genomics study for Alzheimer's Disease (AD). Existing research works mainly depict the association between single nucleotide polymorphisms (SNPs) and the brain endophenotypes via the linear methods, which may introduce high bias due to the simplicity of the models. Since the influence of QTLs on brain endophenotypes is quite complex, it is desired to design the appropriate non-linear models to investigate the associations of genotypes and endophenotypes.
机译:动机:定量性状基因座(QTL)的鉴定对于研究遗传变异和疾病异常之间的因果关系至关重要。 我们专注于识别与阿尔茨海默病(AD)的成像基因组学研究中的脑内内蛋白酶相关的QTL。 现有的研究主要描绘了通过线性方法描绘单个核苷酸多态性(SNP)和脑内骨型之间的关联,这可能引起由于模型的简单性引起的高偏差。 由于QTL对脑内卵型的影响非常复杂,因此希望设计适当的非线性模型来研究基因型和内蛋白酶的关联。

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  • 来源
    《Bioinformatics》 |2018年第17期|共9页
  • 作者单位

    Univ Pittsburgh Elect &

    Comp Engn Pittsburgh PA 15261 USA;

    Univ Pittsburgh Elect &

    Comp Engn Pittsburgh PA 15261 USA;

    Indiana Univ Sch Med Radiol &

    Imaging Sci Indianapolis IN 46202 USA;

    Indiana Univ Sch Med Radiol &

    Imaging Sci Indianapolis IN 46202 USA;

    Indiana Univ Sch Med Radiol &

    Imaging Sci Indianapolis IN 46202 USA;

    Indiana Univ Sch Med Radiol &

    Imaging Sci Indianapolis IN 46202 USA;

    Univ Penn Perelman Sch Med Dept Biostat Epidemiol &

    Informat Philadelphia PA 19104 USA;

    Univ Pittsburgh Elect &

    Comp Engn Pittsburgh PA 15261 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物工程学(生物技术);
  • 关键词

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