title: Emerging patterns and gene expression data.
abstract: One important purpose of conducting gene expression experiments is to understand the correlation of gene expression profiles to disease states. Based on the notion of emerging patterns and an entropy-oriented discretization method, we discover groups of genes that are correlated to disease states in a significant way. In each group, every member gene constrained by a specific expression interval, unanimously occurs only in one type of cells with a maximally large frequency, but never unanimously happens in the other types of cells. According to our studies on the colon tumor dataset, such gene groups (also called patterns) can reach a frequency of 90%, providing good insight into the correlation of gene expression profiles to disease states. The patterns can be used to correctly predict whether a new cell is normal or cancerous.
authors.affiliation: Kent Ridge Digital Labs, 21 Heng Mui Keng Terrace, Singapore, 119613. jinyan@krdl.org.sg
authors.forename: J
authors.initials: J
authors.lastname: Li
authors.forename: L
authors.initials: L
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D003110:Colonic Neoplasms / Q000235:genetics; D019295:Computational Biology; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D023281:Genomics; D006801:Humans; D010363:Pattern Recognition, Automated