'''Presenter: Jennifer Gardy, University of British Columbia, Vancouver, Canada'''

'''Title: Cerebral 2.0: A Cytoscape plugin for the network-based visualization of datasets from multiple experimental conditions'''

Authors:
 * Jennifer Gardy, Centre for Microbial Diseases & Immunity Research, University of British Columbia
 * Aaron Barsky, Department of Computer Science, University of British Columbia
 * Robert Kincaid, Agilent Labs, Agilent Technologies
 * Tamara Munzner, Department of Computer Science, University of British Columbia
 * Robert Hancock, Centre for Microbial Diseases & Immunity Research, University of British Columbia

Abstract:
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Cerebral v.1.0 (2007) uses subcellular localization annotations to perform a constrained layout algorithm, automatically creating a layered cell-centric network view, placing nodes in the region of the screen corresponding to the appropriate subcellular localization. Recently we extended Cerebral to visualize and overlay data from multiple quantitative experiments. Through a set of coordinated views, users can simultaneously view both experimentally-measured data and the network representation of the biological model. Combined with the localization-based layout, users can view/analyze their data within multiple contexts simultaneously: biomolecular interactions, subcellular localization and quantitative measurements.
Small multiple views provide an overview of each experimental condition  – the measurements associated with different experimental treatments or timepoints are used to colour the nodes in the network. Two conditions can be selected and used to generate a difference view, in which the network is coloured according to the difference between the measurements at each condition. The parallel coordinates view provides a profile-based view of the experimental data, with the measurements plotted on a line graph that can be modified by the user and clustered using an interactive, adjustable k-means tool.
Cerebral is implemented as a freely available Cytoscape plugin and is fully integrated into the InnateDB biomolecular interaction database.
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