Inferring genetic networks and identifying compound mode of action via expression profiling
Abstract
The complexity of cellular gene, protein, and metabolite networks can hinder attempts to elucidate their structure and function. To address this problem, we used systematic transcriptional perturbations to construct a first-order model of regulatory interactions in a nine-gene subnetwork of the SOS pathway in Escherichia coli. The model correctly identified the major regulatory genes and the transcriptional targets of mitomycin C activity in the subnetwork. This approach, which is experimentally and computationally scalable, provides a framework for elucidating the functional properties of genetic networks and identifying molecular targets of pharmacological compounds.
Citations
Inferring the connectivity of a regulatory network from mRNA quantification in Synechocystis PCC6803
A microarray data-based semi-kinetic method for predicting quantitative dynamics of genetic networks
Systems level analysis of osteoclastogenesis reveals intrinsic and extrinsic regulatory interactions
Related Concepts
Related Feeds
CZI Human Cell Atlas Seed Network
The aim of the Human Cell Atlas (HCA) is to build reference maps of all human cells in order to enhance our understanding of health and disease. The Seed Networks for the HCA project aims to bring together collaborators with different areas of expertise in order to facilitate the development of the HCA. Find the latest research from members of the HCA Seed Networks here.