Molecular Networks and Complex Diseases

Many human diseases are based on a set of complex interactions among multiple genetic and environmental factors. Recent developments in biotechnology have enabled interrogation of the cell at various levels leading to many types of “omic” data that provide valuable information on these factors and their interactions. These data include (1) genomic data, which reveals possible genetic factors involved in disease, (2) transcriptomic data, which reveals changes in regulation of gene expression, and (3) proteomic data, which reveals irregularities in the amount of functional proteins in affected tissues. While these data are very useful in understanding differences between disease phenotypes, they provide information at the level of a single molecular type. To integrate these disparate data types, molecular network analysis is invaluable in uncovering the relations between disparate molecular targets and understanding disease development and progression at the systems level. This chapter provides an overview of current findings on the systems biology of human diseases in the context of molecular networks and outlines current computational approaches in network biology of human diseases.