In This Issue

Determining which gene interactions yield a particular gene expression pattern is one of the great challenges of biology. Because the number of genes far exceeds the number of expression profiles, piecing together this network is particularly tricky. Using the principle of entropy maximization, Timothy Lezon et al. analyzed microarray expression data from Saccharomyces cerevisiae and identified genes coding for proteins involved in switching genes on or off as the cells oscillate between high and low metabolism when their diet is restricted. The method enabled the authors to identify key regulatory genes coordinating the metabolic state and cell division with the availability of nutrients. Lezon et al. were also able to identify genes involved in mitochondrial maintenance, pH regulation, cell wall biosynthesis, gene transcription, and DNA replication and repair. This method may improve the ability to sift through microarray expression data from any organism to identify critical genes.—B.T.