The rapid development in biotechnology has created opportunities to examine biological systems at unprecedented quantitative levels. One problem which has attracted the attention of many theorists recently is the regulation of gene expression for model biological systems such as E. coli and yeast. Through pains-taking experiments over the years, a great deal is known about the transcription factors (TF) and their binding sites that modulate the expression of individual genes. Data of this type has allowed construction of transcription networks on the genome scale in a few cases. Yet knowing the wiring among the transcription factors is not sufficient to determine the actual level of expression under various cell environment and external stimuli. Our current focus includes comparison of high-throughput microarray expression data with literature-based regulation networks, and theoretical analysis of the topology and design principles of transcription control network. Students interested in statistical physics/bioinformatics/control theory may apply.