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Assessing the Exceptionality of Coloured Motifs in Networks

机译:评估网络中彩色图案的异常性

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摘要

Various methods have been recently employed to characterise the structure of biological networks. In particular, the concept of network motif and the related one of coloured motif have proven useful to model the notion of a functional/evolutionary building block. However, algorithms that enumerate all the motifs of a network may produce a very large output, and methods to decide which motifs should be selected for downstream analysis are needed. A widely used method is to assess if the motif is exceptional, that is, over- or under-represented with respect to a null hypothesis. Much effort has been put in the last thirty years to derive -values for the frequencies of topological motifs, that is, fixed subgraphs. They rely either on (compound) Poisson and Gaussian approximations for the motif count distribution in Erdös-Rényi random graphs or on simulations in other models. We focus on a different definition of graph motifs that corresponds to coloured motifs. A coloured motif is a connected subgraph with fixed vertex colours but unspecified topology. Our work is the first analytical attempt to assess the exceptionality of coloured motifs in networks without any simulation. We first establish analytical formulae for the mean and the variance of the count of a coloured motif in an Erdös-Rényi random graph model. Using simulations under this model, we further show that a Pólya-Aeppli distribution better approximates the distribution of the motif count compared to Gaussian or Poisson distributions. The Pólya-Aeppli distribution, and more generally the compound Poisson distributions, are indeed well designed to model counts of clumping events. Altogether, these results enable to derive a -value for a coloured motif, without spending time on simulations.
机译:最近已经采用了各种方法来表征生物网络的结构。尤其是,网络主题的概念和相关的彩色主题已被证明可用于对功能/进化构件的概念进行建模。但是,枚举网络中所有主题的算法可能会产生非常大的输出,因此需要用于确定应选择哪些主题进行下游分析的方法。一种广泛使用的方法是评估主题是否是例外的,即相对于无效假设而言是过度代表还是不足代表。在过去的三十年中,已经做出了很多努力来得出拓扑图案(即固定子图)的频率值。他们依靠(复合)泊松和高斯近似来获得Erdös-Rényi随机图中的图案计数分布,或者依赖于其他模型中的模拟。我们专注于图形主题对应于彩色主题的不同定义。彩色图案是具有固定顶点颜色但未指定拓扑的连接子图。我们的工作是在没有任何模拟的情况下,首次评估分析彩色图案在网络中的特殊性的尝试。我们首先为Erdös-Rényi随机图模型中的彩色图案计数的均值和方差建立分析公式。使用该模型下的仿真,我们进一步证明,与高斯或泊松分布相比,Pólya-Aeppli分布更好地近似了主题数的分布。实际上,Pólya-Aeppli分布以及更一般的复合Poisson分布都经过精心设计,可以对结块事件计数进行建模。总而言之,这些结果能够得出彩色图案的-值,而无需花费时间进行仿真。

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