title: Mapping the gene expression universe.
abstract: Methods to globally survey gene expression provide valuable insights into gene function during development. In particular, comprehensive in situ hybridization studies have demonstrated that gene expression patterns are extraordinarily diverse and new imaging techniques have been introduced to capture these patterns with higher resolution at the tissue, cellular, and subcellular levels. The analysis of massive image databases can be greatly facilitated by computer vision techniques once annotated image sets reach the crucial mass sufficient to train the computer in pattern recognition. Ultimately, genome-wide atlases of gene expression during development will record gene activity in living animals with at least cellular resolution and in the context of morphogenetic events. These emerging datasets will lead to great advances in the field of comparative genomics and revolutionize our ability to decipher and model developmental processes for a variety of organisms.
authors.affiliation: Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada. eric.lecuyer@utoronto.ca
authors.forename: Eric
authors.initials: E
authors.lastname: Lécuyer
authors.forename: Pavel
authors.initials: P
authors.lastname: Tomancak
mesh_terms: D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D023281:Genomics / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D017403:In Situ Hybridization / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods