A linear discrete dynamic system model for temporal gene interaction and regulatory network influence in response to bioethanol conversion inhibitor HMF for ethanologenic yeast

Authors:
Mingzhou Joe Song;Z. Lewis Liu
Affiliations:
Department of Computer Science, New Mexico State University, Las Cruces, NM;National Center for Agricultural Utilization Research, U.S. Department of Agriculture, Agriculture Research Service, Peoria, Illinois
Venue:
RECOMB'06 Proceedings of the joint 2006 satellite conference on Systems biology and computational proteomics
Year:
2006

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Abstract

A linear discrete dynamic system model is constructed to represent the temporal interactions among significantly expressed genes in response to bioethanol conversion inhibitor 5-hydroxymethylfurfural for ethanologenic yeast Saccharomyces cerevisiae. This study identifies the most significant linear difference equations for each gene in a network. A log-time domain interpolation addresses the non-uniform sampling issue typically observed in a time course experimental design. This system model also insures its power stability under the normal condition in the absence of the inhibitor. The statistically significant system model, estimated from time course gene expression measurements during the earlier exposure to 5-hydroxymethylfurfural, reveals known transcriptional regulations as well as potential significant genes involved in detoxification for bioethanol conversion by yeast.