Dynamic modeling of gene expression data. Journal   Proceedings of the National Academy of Sciences of the United States of America. Citation   Proc Natl Acad Sci U S A. 98(4):1693-8 Publication date   2001 Feb 13 Authors   Holter NS Maritan A Cieplak M Fedoroff NV Banavar JR Investigators   Jayanth Banavar Nina Fedoroff MeSH headings   Gene Expression Profiling Models, Genetic Abstract   We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small. Medline ID   21117100