I will describe various efforts that we at the Institute for Systems Biology have undertaken to model the pathways and dynamics of systems in organisms from yeast to human. I will focus on our system for network inference and modeling of the regulatory network of Halobacterium, an organism that thrives in hypersaline environments. Our inference procedure consists of three major components: cMonkey (a method for learning co-regulated biclusters and pathways), the Inferelator (a regulatory network inference procedure) and the Gaggle (a system for visualizing high-throughput data and managing the results of the statistical analyses). These three components, which have been described individually, now comprise an integrated system that has been applied to Halobacterium and to several other model organisms. In Halobacterium, our inferred network was shown to be predictive of 130 newly collected microarray experiments and has been partially validated using ChIP-chip (protein-DNA binding assays). This effort represents one of the first coordinated functional genomics efforts in archaea and in particular, under hypersaline conditions.
Here is some background reading for those who are interested: