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Network Topological Reordering Revealing Systemic Patterns in Yeast Protein Interaction Networks

机译:网络拓扑重新排序揭示酵母蛋白互动网络中的全身模式

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Identifying candidate genes/proteins involved in human disease specific molecular pathways or networks has been a primary focus of biomedical research. Although node ranking and graph clustering methods can help identify localized topological properties in a network, it remains unclear how the results should be interpreted in biological functional context in systems-level. In complex biomolecular interaction networks, biomolecular entities may not have absolute ranks or clear cluster boundary among them. We presented Ant Colony Optimization Reordering (ACOR) method to examine emerging network properties. The task of reordering nodes is represented as the problem of finding optimal density distribution of "ant colony" on all nodes of the network. We applied ACOR method to re-analyze a yeast protein-protein interaction (PPI) network annotated with functional information (i.e., lethality), which revealed intriguing systems-level functional features.
机译:鉴定参与人类疾病特异性分子途径或网络的候选基因/蛋白是生物医学研究的主要焦点。虽然节点排名和图形聚类方法可以有助于识别网络中的本地化拓扑属性,但它仍然尚不清楚如何在系统级别的生物学功能上下文中解释结果。在复杂的生物分子相互作用网络中,生物分子实体可能在其中不具有绝对排名或清晰的簇边界。我们提出了蚁群优化重新排序(ACOR)方法来检查新兴网络属性。重新排序节点的任务表示为在网络的所有节点上找到“蚁群”的最佳密度分布的问题。我们应用ACOR方法重新分析具有功能信息(即致死性)的酵母蛋白 - 蛋白质相互作用(PPI)网络,其揭示了有趣的系统级功能特征。

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