With the popularization of microarray experiments in biomedical laboratories, how to make context-specific knowledge discovery from expression data becomes a hot topic. While the static “reference networks” for key model organisms are nearly at hand, the endeavors to recover context-specific network modules are still at the beginning. Currently, this is achieved through filtering existing edges of the ensemble reference network or constructing gene networks ab initio. In this paper, we briefly review recent progress in the field and point out some research directions awaiting improved work, including expression-data-guided revision of reference networks.
