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METHODS AND SYSTEMS FOR CUSTOMIZABLE CLUSTERING OF SUB-NETWORKS FOR BIOINFORMATICS AND HEALTH CARE APPLICATIONS

机译:用于生物信息学和卫生保健应用的子网络的可自定义集群的方法和系统

摘要

Methods and devices for clustering a plurality of sub-networks of a larger interaction network using an enhanced hierarchical clustering algorithm are disclosed. The methods provide expression based sub-network generation using differentially expressed markers. The enhanced hierarchical clustering algorithm clusters the generated sub-networks based on a user defined customizable similarity coefficient. The methods use non-Boolean links to cluster similar sub-networks. This provides consideration of indirect relationships among sub-networks. The customizable similarity coefficient enables the methods to be used for diverse applications such as biomarker detection, patient stratification, personalized therapy, drug efficacy prediction, genetic similarity analysis in genetic diseases. The methods enable patient grouping based on the enhanced hierarchical clustering algorithm.
机译:公开了用于使用增强的分层聚类算法对较大的交互网络的多个子网进行聚类的方法和设备。该方法使用差异表达的标记物提供基于表达的子网生成。增强的分层聚类算法基于用户定义的可定制相似系数对生成的子网进行聚类。该方法使用非布尔链接来对相似的子网进行聚类。这提供了子网之间的间接关系的考虑。可定制的相似系数使这些方法可用于多种应用,例如生物标志物检测,患者分层,个性化治疗,药物疗效预测,遗传疾病中的遗传相似性分析。该方法使得能够基于增强的分层聚类算法对患者进行分组。

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