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Nonlinear modeling of gene networks from time series gene expression data when

机译:根据时间序列基因表达数据对基因网络进行非线性建模

摘要

Embodiments of this invention include application of new inferential methods to analysis of complex biological information, including gene networks. In some embodiments, time course data obtained simultaneously for a number of genes in an organism. New methods include modifications of Bayesian inferential methods and application of those methods to determining cause and effect relationships between expressed genes, and in some embodiments, for determining upstream effectors of regulated genes. Additional modifications of Bayesian methods include use of time course data to infer causal relationships between expressed genes. Other embodiments include the use of bootstrapping methods and determination of edge effects to more accurately provide network information between expressed genes. Information about gene networks can be stored in a memory device and can be transmitted to an output device, or can be transmitted to remote location.
机译:本发明的实施例包括将新的推论方法应用于分析复杂的生物信息,包括基因网络。在一些实施方案中,同时获得生物体中许多基因的时程数据。新方法包括贝叶斯推理方法的修改和那些方法的应用,以确定表达的基因之间的因果关系,并且在一些实施方案中,用于确定调节基因的上游效应子。贝叶斯方法的其他修改包括使用时程数据来推断表达的基因之间的因果关系。其他实施方案包括使用自举方法和确定边缘效应以更准确地提供表达的基因之间的网络信息。有关基因网络的信息可以存储在存储设备中,可以传输到输出设备,也可以传输到远程位置。

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