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Coupling Regulatory Networks and Microarays: Revealing Molecular Regulations of Breast Cancer Treatment Responses

机译:耦合的监管网络和微射线:揭示乳腺癌治疗反应的分子调控。

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Moving towards the realization of genomic data in clinical practice, and following an individualized healthcare approach, the function and regulation of genes has to be deciphered and manifested. Two of the most significant forms of molecular data come form microarray gene expression sources, and gene interactions sources - as encoded in Gene Regulatory Networks (GRNs). The usual computational task is the gene selection procedure with the GRNs to be mainly utilized for annotation and enrichment purposes. In this study we present a novel perception of these resources. Initially we locate all functional path-modules encoded in GRNs and we try to assess which of them are compatible and match the gene-expression profiles of samples that belong to different phenotypes. The differential power of the selected path-modules is computed and their biological relevance is assessed. The whole approach was applied on a set of microarray studies with the target of revealing putative regulatory mechanisms that govern and putatively guide the treatment responses of BRCA patients. The results were quite satisfactory according to their biological and clinical relevance.
机译:朝着在临床实践中实现基因组数据的方向发展,并遵循个性化的医疗保健方法,必须破译和展现基因的功能和调节。分子数据的两种最重要形式来自微阵列基因表达源和基因相互作用源-如基因调控网络(GRN)所编码。通常的计算任务是使用带有GRN的基因选择程序,该程序主要用于注释和富集目的。在这项研究中,我们提出了对这些资源的新颖理解。最初,我们找到在GRN中编码的所有功能路径模块,然后尝试评估它们中的哪些是兼容的,并匹配属于不同表型的样品的基因表达谱。计算所选路径模块的差分功率,并评估其生物学相关性。整个方法应用于一系列微阵列研究,其目标是揭示推测的调控机制,该机制可控制和假定地指导BRCA患者的治疗反应。根据它们的生物学和临床相关性,结果是令人满意的。

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