Discovering Gene Clusters via Integrated Analysis on Time-Series and Group-Comparative Microarray Datasets

In this paper, we propose a novel gene clustering method named TGmix through integrated analysis on two types of datasets, namely the time-series and two-group microarray datasets. The goal of the proposed method is to discover genes as biomarkers that have similar expression profiles in time-series conditions and are also significantly differentially expressed in two-group conditions. We applied the proposed method to microarray datasets for rat´s wound healing experiment, and the genes discovered in the same cluster conform to the analysis goal with related biological functions