The phenotypic response of a cell results from a well orchestrated web of complex interactions which propagate from the genetic architecture through the metabolic flux network. To rationally design cell factories which carry out specific functional objectives by controlling this hierarchical system is a challenge. Transcriptome analysis, the most mature high-throughput measurement technology, has been readily applied In strain improvement programs in an attempt to Identify genes involved in expressing a given phenotype. Unfortunately, while differentially expressed genes may provide targets for metabolic engineering, phenotypic responses are often not directly linked to transcriptional patterns, This limits the application of genome-wide transcriptional analysis for the design of cell factories. However, improved tools for integrating transcriptional data with other high-throughput measurements and known biological interactions are emerging. These tools hold significant promise for providing the framework to comprehensively dissect the regulatory mechanisms that identify the cellular control mechanisms and lead to more effective strategies to rewire the cellular control elements for metabolic engineering.