title: Inferring signalling networks from images.
abstract: The mapping of signalling networks is one of biology's most important goals. However, given their size, complexity and dynamic nature, obtaining comprehensive descriptions of these networks has proven extremely challenging. A fast and cost-effective means to infer connectivity between genes on a systems-level is by quantifying the similarity between high-dimensional cellular phenotypes following systematic gene depletion. This review describes the methodology used to map signalling networks using data generated in the context of RNAi screens.
authors.affiliation: Chester Beatty Laboratories, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London, UK, SW3 6JB.
authors.forename: L
authors.initials: L
authors.lastname: Evans
authors.forename: H
authors.initials: H
authors.lastname: Sailem
authors.forename: P Pascual
authors.initials: PP
authors.lastname: Vargas
authors.forename: C
authors.initials: C
authors.lastname: Bakal
mesh_terms: D000818:Animals; D002468:Cell Physiological Phenomena; D002478:Cells, Cultured; D003584:Cytological Techniques / Q000379:methods*; D004330:Drosophila; D020868:Gene Silencing; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008853:Microscopy / Q000379:methods*; D015398:Signal Transduction
keywords: Heterogeneity; RNAi; image analysis; morphological signatures; signalling networks