Dynamic modeling of gene expression data

Abstract

We describe the time evolution of gene expression levels by using a\rtime translational matrix to predict future expression levels of genes\rbased on their expression levels at some initial time. We deduce the\rtime translational matrix for previously published DNA microarray gene\rexpression data sets by modeling them within a linear framework by\rusing the characteristic modes obtained by singular value\rdecomposition. The resulting time translation matrix provides a measure\rof the relationships among the modes and governs their time evolution.\rWe show that a truncated matrix linking just a few modes is a good\rapproximation of the full time translation matrix. This finding\rsuggests that the number of essential connections among the genes is\rsmall.\r