Modeling gene expression control using Omes Law

Abstract

Mol Syst Biol. 2: 2006.0013 The binding of transcription factors (TFs) to specific sites in the genome is a crucial step in the molecular process controlling gene expression. The in vitro sequence specificity of these regulatory proteins can generally be well represented by consensus DNA motifs or slightly more sophisticated sequence profiles called position‐specific scoring matrices. These are widely used to scan genome sequences in order to find novel transcriptional target genes. Unfortunately, usually only a small fraction of the ‘hits’ thus obtained are functional in vivo , where local chromatin structure and TF–TF interactions come into play. Taking into account the context provided by the surrounding noncoding DNA is therefore essential. In a recent study currently published in Molecular Systems Biology, Nguyen and D'haeseleer (2006) present a promising strategy for determining which context features are most important for a given TF binding motif. Their approach belongs to a growing class of methods that fit simple mathematical models of transcription regulation to DNA microarray data to map gene regulation networks. Many of the molecular players that govern gene expression are known, but our knowledge about their interactions with the DNA and with each other is very incomplete. Information about the gene regulatory network is only implicitly represented in the large volume of functional genomics data now available to us. The strengths of the ‘arrows’ between TFs and their target genes and the condition‐specific activities of the regulatory ‘nodes’ need to be inferred by computational means. A detailed mathematical model that accurately describes the molecular …