Complex diseases are caused by changes in structural and functional genome signaling architecture. Although all classes of mutations can be identified with modern high -throughput technologies, understanding gene expression regulatory networks and transduction interactions represents a daunting challenge. Advances in dynamic network biology, systems computational biology, and predictive network models pave now the way to achieve clinical personalized medicine. Sophisticated genome-based diagnostics and prognostic and predictive biomarkers may emerge by relating personal genomic discoveries with disease phenotypes (clinical outcome). |
