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Using networks to measure similarity between genes: association index selection
Juan I Fuxman Bass1, Alos Diallo, Justin Nelson
11] 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.
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.
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