利用网络测量基因间相似性：关联指数选择。
Using networks to measure similarity between genes: association index selection.
机构信息
1] Program in Systems Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA. [2] Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
出版信息
Nat Methods. 2013 Dec;10(12):1169-76. doi: 10.1038/nmeth.2728.
Abstract
Biological networks can be used to functionally annotate genes on the basis of interaction-profile similarities. Metrics known as association indices can be used to quantify interaction-profile similarity. We provide an overview of commonly used association indices, including the Jaccard index and the Pearson correlation coefficient, and compare their performance in different types of analyses of biological networks. We introduce the Guide for Association Index for Networks (GAIN), a web tool for calculating and comparing interaction-profile similarities and defining modules of genes with similar profiles.
摘要
生物网络可用于根据相互作用谱相似性对基因进行功能注释。可以使用称为关联指数的指标来量化相互作用谱相似性。我们提供了常用关联指数的概述，包括 Jaccard 指数和 Pearson 相关系数，并比较了它们在生物网络的不同类型分析中的性能。我们引入了网络关联指数指南 (GAIN)，这是一个用于计算和比较相互作用谱相似性以及定义具有相似谱的基因模块的网络工具。
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