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Towards constructing “Super Gene Sets” regulatory networks

机译:建设“超基因套”监管网络

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In this article, we described a new computational framework to construct “Super Gene Sets”-Pathways, Annotated list, and Gene signatures (PAGs), regulatory (r-type) PAG-PAG relationships. To construct PAGs, we aggregate singleton PAGs (sPAGs) upstream/downstream of a common shared multi-gene PAG (mPAGs). Then, we iteratively remove a member gene to calculate its Cohesion Coefficient (CoCo), which helps assess the degree of biological relevance beyond random chance, until the CoCo score achieves the maximal value at a specific level. The new relationship between aggregated mPAG (m'PAG) and the shared mPAG will, therefore, have distinct m'PAG-mPAG relationships. Our results suggest the following. First, the new m'PAGs have sufficiently high CoCo scores, suggesting high biological relevance, and distinct gene ontology annotations different from their regulated PAG targets; however, there are significant enrichments of shared GO annotations between each pair of identified m'PAG-mPAG relationships. Second, new m'PAGs are relatively robust against data noise based on noise characteristic simulations. Third, by applying our framework to real cancer microarray analysis data, we demonstrated that our new framework is effective in helping build multi-scale biomolecular systems models that are easy to interpret by biologists.
机译:在本文中,我们描述了一种构建“超基因集”--Patchways,注释列表和基因签名(PAG),调节(R型)PAG-PAG关系的新计算框架。为了构建PAG,我们将单例PAG(SPAG)聚集在普通共享多基因PAG(MPAG)的上游/下游。然后,我们迭代地去除成员基因以计算其凝聚力系数(COCO),这有助于评估随机机会之外的生物相关程度,直到COCO得分在特定水平处实现最大值。因此,聚合MPAG(M'PAG)与共享MPAG之间的新关系将具有不同的M'PAG-MPAG关系。我们的结果表明了以下内容。首先,新的M'Pags具有足够高的可可评分,表明高生物相关性,不同的基因本体学注释与其受管制的PAG目标不同;但是,在每对识别的M'PAG-MPAG关系之间存在显着的共享GO注释的浓缩。其次,新的M'Pags对基于噪声特性模拟的数据噪声相对稳健。第三,通过将我们的框架应用于真实的癌症微阵列分析数据,我们证明了我们的新框架有效帮助构建易于解释的多级生物分子系统模型。

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