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    • 2. 发明申请
    • Nonlinear modeling of gene networks from time series gene expression data
    • 基因网络的时间序列基因表达数据的非线性建模
    • US20050055166A1
    • 2005-03-10
    • US10716330
    • 2003-11-18
    • Satoru MiyanoSeiya ImotoSun Kim
    • Satoru MiyanoSeiya ImotoSun Kim
    • G01N33/48G01N33/50G06F19/00G06N5/04G06N7/00
    • G06N7/005G16B5/00G16B25/00G16B40/00
    • 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.
    • 本发明的实施例包括应用新的推理方法来分析复杂的生物信息,包括基因网络。 在一些实施方案中,对于生物体中的许多基因同时获得的时间过程数据。 新方法包括贝叶斯推理方法的修改和这些方法的应用以确定表达基因之间的因果关系,并且在一些实施方案中用于确定受调节基因的上游受体。 贝叶斯方法的其他修改包括使用时间过程数据来推断表达基因之间的因果关系。 其他实施例包括使用自举方法和确定边缘效应以更准确地提供表达基因之间的网络信息。 关于基因网络的信息可以存储在存储设备中,并且可以被传输到输出设备,或者可以被发送到远程位置。