title: Gene function inference from gene expression of deletion mutants.
abstract: Expression data from knockout mutants is a powerful tool for gene function inference, permitting observation of the phenotype of a deleted gene on the organismal scale. A computational method is demonstrated herein to assess gene function from gene expression measured in deletion mutants using Bayesian decomposition, a matrix factorization technique that permits the extraction of patterns and functional units from the data, i.e., sets of genes belonging to the same pathways shared by sets of knockout mutants. ClutrFree, a cluster visualization program is used to aid in the interpretation of functional units and the assessment of gene functions for a subset of unknown genes.
authors.affiliation: University of Pennsylvania School of Medicine, Philadelphia, USA.
authors.forename: Ghislain
authors.initials: G
authors.lastname: Bidaut
mesh_terms: D001499:Bayes Theorem; D030541:Databases, Genetic; D017353:Gene Deletion; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D005800:Genes, Fungal; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D012441:Saccharomyces cerevisiae / Q000235:genetics; D012984:Software