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Towards constructing “Super Gene Sets” regulatory networks

机译:致力于构建“超级基因集”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,我们描述了一种新的计算框架,用于构建“超级基因集”-途径,注释列表和基因签名(PAG),调节性(r型)PAG-PAG关系。为了构建PAG,我们在一个共享的共享多基因PAG(mPAG)的上游/下游汇总了单例PAG(sPAG)。然后,我们迭代地删除一个成员基因以计算其内聚系数(CoCo),这有助于评估超出随机机会的生物学相关性程度,直到CoCo得分达到特定水平的最大值为止。因此,聚合的mPAG(m'PAG)与共享的mPAG之间的新关系将具有截然不同的m'PAG-mPAG关系。我们的结果表明以下几点。首先,新的m'PAG具有足够高的CoCo分数,表明具有较高的生物学相关性,并且有别于其调控的PAG靶标的独特基因本体注释;但是,在每对已识别的m'PAG-mPAG关系之间,共享的GO注释显着丰富。其次,基于噪声特性仿真,新的m'PAG具有相对强大的抗数据噪声能力。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可以有效地帮助建立生物学家易于解释的多尺度生物分子系统模型。

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