Global modeling of transcriptional responses in interaction networks
This work addresses the challenge of understanding unknown regulatory processes in cell biology for researchers in genomics and systems biology, but it is incremental as it builds on existing network analysis methods.
The authors tackled the problem of modeling transcriptional responses in gene interaction networks across physiological conditions, introducing a method that identifies connected network regions with coordinated responses, validated on a human pathway network to reveal coherent functional patterns.
Motivation: Cell-biological processes are regulated through a complex network of interactions between genes and their products. The processes, their activating conditions, and the associated transcriptional responses are often unknown. Organism-wide modeling of network activation can reveal unique and shared mechanisms between physiological conditions, and potentially as yet unknown processes. We introduce a novel approach for organism-wide discovery and analysis of transcriptional responses in interaction networks. The method searches for local, connected regions in a network that exhibit coordinated transcriptional response in a subset of conditions. Known interactions between genes are used to limit the search space and to guide the analysis. Validation on a human pathway network reveals physiologically coherent responses, functional relatedness between physiological conditions, and coordinated, context-specific regulation of the genes. Availability: Implementation is freely available in R and Matlab at http://netpro.r-forge.r-project.org