TDAC: Co-expressed gene pattern finding using attribute clustering

Abstract

An effective unsupervised method (TDAC) is proposed for identification of biologically relevant co-expressed patterns. Effectiveness of TDAC is established in comparison to its other competing algorithms over four publicly available benchmark gene expression datasets in terms of both internal and external validity measures.