PHOCOS: inferring multi-feature phenotypic crosstalk networks.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Jun 15, 2016
Abstract
MOTIVATION: Quantification of cellular changes to perturbations can provide a powerful approach to infer crosstalk among molecular components in biological networks. Existing crosstalk inference methods conduct network-structure learning based on a single phenotypic feature (e.g. abundance) of a biomarker. These approaches are insufficient for analyzing perturbation data that can contain information about multiple features (e.g. abundance, activity or localization) of each biomarker.