Toward the discovery of itemsets with significant variations in gene expression matrices

Abstract

Gene expression matrices are numerical tables that describe the level of expression of genes in different situations, characterizing their behaviour. Biologists are interested in identifying groups of genes presenting similar quantitative variations of expression. This paper presents new syntactic constraints for itemset mining in particular Boolean gene expression matrices. A two dimensional gene expression profile representation is introduced and adapted to itemset mining allowing one to control gene expression. Syntactic constraints are used to discover itemsets with significant expression variations from a large collection of gene expression profiles. © Springer-Verlag Berlin Heidelberg 2011.