title: Visualization and clustering of high-dimensional transcriptome data using GATE.
abstract: The potential gains from advances in high-throughput experimental molecular biology techniques are commonly not fully realized since these techniques often produce more data than can be easily organized and visualized. To address these problems, GATE (Grid-Analysis of Time-Series Expression) was developed. GATE is an integrated software platform for the analysis and visualization of high-dimensional time-series datasets, which allows flexible interrogation of time-series data against a wide range of databases of prior knowledge, thus linking observed molecular dynamics to potential genetic, epigenetic, and signaling mechanisms responsible for observed dynamics. This article provides a brief guide to using GATE effectively.
authors.affiliation: Centre for Human Development, Stem Cells and Regeneration, Institute of Developmental Sciences, University of Southampton, Southampton, SO16 6YD, UK.
authors.forename: Patrick S
authors.initials: PS
authors.lastname: Stumpf
authors.forename: Ben D
authors.initials: BD
authors.lastname: MacArthur
mesh_terms: D056808:Biostatistics / Q000379:methods*; D016000:Cluster Analysis; D003196:Computer Graphics; D020869:Gene Expression Profiling / Q000379:methods*; D012984:Software