Abstract

There has been a recent surge of interest in uncovering the organizing principles of biological systems ranging from signalling to neuronal networks. While advances in this direction have largely focused on understanding how topological properties and network organization characterize complex biological systems, the dynamics of the underlying entities (i.e., nodes in the network) and their role in systems behavior remain poorly understood. In this presentation, I will describe our recent work investigating the genome-scale dynamics of the transcriptional regulatory network in yeast. In particular, by integrating the information on the hierarchical organization of transcription factors in the network with diverse datasets that characterize the dynamics of transcription, translation and noise in gene expression, we identify general principles of transcriptional network dynamics. We suggest that the interplay between the inherent hierarchy of the network and the dynamics of the transcription factors are critical for making the transcription network both robust and adaptable. In addition, we observe that the expression levels of key transcription factors are variable (noisy) between individuals in a population of cells. Such behaviour may be advantageous as it may permit differential utilization of the same underlying network in distinct members of a population. We anticipate that many of the concepts presented here will apply to other biological networks, including complex sub-systems in higher eukaryotes.