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A dividing-and-matching algorithm to detect conserved protein complexes via local network alignment

机译:一种通过局部网络比对检测保守蛋白复合物的匹配算法

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Local network alignment is an effective way to comparatively analyze a pair of protein-protein interaction (PPI) networks so as to identify the common subnetworks (conserved protein complexes) across species, which helps us better understand the structure, function and evolution of biological cells. In this work, we propose a new dividing-and-matching method named by DAMAlign to detect conserved protein complexes via local network alignment. DAMAlign firstly partitions one of PPI network into subnetworks and then these subnetworks are mapped to the other PPI network to find common connected components. In the course of finding common connected components, DAMAlign adopts a lenient criteria that is we locally extend a pair of homologous proteins if there exists at least one path of length not larger than 2 to connect one of node in the homologous protein pair in its corresponding network. We implement network alignment between S. cerevisiae and D. melanogaster. The experimental results show that DAMAlign outperforms other existing methods in recovering known protein complexes. Moreover, the conserved protein complexes that are detected by DAMAlign from different PPI networks are also functional similar in terms of their GO semantic similarity.
机译:局部网络比对是比较分析一对蛋白质-蛋白质相互作用(PPI)网络,以识别物种间常见的子网络(保守的蛋白质复合物)的有效方法,这有助于我们更好地了解生物细胞的结构,功能和进化。在这项工作中,我们提出了一种新的划分匹配方法,即DAMAlign,可以通过本地网络比对来检测保守的蛋白质复合物。 DAMAlign首先将一个PPI网络划分为多个子网络,然后将这些子网络映射到另一个PPI网络,以查找公共连接的组件。在寻找共同的连接组件的过程中,DAMAlign采用了宽大的标准,即如果存在至少一条长度不大于2的路径以将其对应的同源蛋白对中的一个节点连接起来,我们会局部扩展一对同源蛋白网络。我们实现酿酒酵母和黑腹果蝇之间的网络对齐。实验结果表明,DAMAlign在回收已知蛋白质复合物中的性能优于其他现有方法。此外,就其GO语义相似性而言,由DAMAlign从不同的PPI网络检测到的保守蛋白复合物在功能上也相似。

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