Correlation patterns in gene expressions along the cell cycle of yeast

Abstract

Currently available genome-wide expression measurements and the respective data bases represent the reliable entry information for gene interaction research. In order to unravel the collective behavior of genes, methods and approaches pertinent to complex dynamical systems are necessary. Using the network theory,we study correlation patterns in the time series of gene expressions of Yeast measured along the cell cycle. We select a subset of genes by their leading participation in the scale-invariant features of the expression data. Applying standard filtering of the correlation matrix reveals inhomogeneous mesoscopic structure of the related graph with several well defined modules of genes. The findings are corroborated by the spectral analysis of the correlation matrix and the eigenvector localization on the graph. The topologically distinct groups of genes which are co-expressed within a given phase of the cell cycle belong to different functional categories but often share the same localization, i.e., nucleus, cytoplasm, or mitochondria, inside the cell. © 2009 Springer-Verlag Berlin Heidelberg.