计算机科学
四分位数
集团
表达式(计算机科学)
西格玛
构造(python库)
渗透(认知心理学)
交互网络
蛋白质-蛋白质相互作用
度量(数据仓库)
计算生物学
数据挖掘
基因
数学
生物
遗传学
组合数学
物理
计算机网络
统计
置信区间
量子力学
神经科学
程序设计语言
作者
Soheir Noori,Nabeel H. Al-A’araji,Eman S. Al-Shamery
出处
期刊:Proteins
[Wiley]
日期:2022-01-22
卷期号:90 (5): 1219-1228
被引量:1
摘要
Real protein interaction network (PIN) is dynamic. Researchers created dynamic PIN by combining static PIN with gene expression data to explain the dynamicity evolution of protein interactions. However, all available approaches failed to recognize low- or high-expression proteins as active proteins. Therefore, determining an adequate threshold is one of the system's biological challenges. In this study, a quartile one (q-one) method is proposed to determine the active time points for each protein according to its expression value's features and construct dynamic protein interaction networks (DPINs) in which a protein is added to the network if it is active in two successive time points. This leads to reduce the number of DPINs to half. The efficiency of the q-one approach and three-sigma (3-sigma) method in detecting protein complexes is evaluated using Markov cluster method, clique percolation method, and ClusterONE algorithms. In most cases, q-one outperforms the 3-sigma method in recall, precision and F-measure. This is in addition to its ability to reveal the dynamicity within the protein-protein interaction network and identify essential proteins.
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