Molecular Network Analysis and Applications

In the post-genomic era of systems biology, the cell itself can be viewed as a complex network of interacting proteins, nucleic acids, and other biomolecules (Hartwell et al., 1999; Eisenberg et al., 2000). Graph representation adopted from mathematics and computer science has been widely applied to describe various molecular systems including protein interaction maps, metabolites and reactions, transcriptional regulation maps, signal transduction pathways, and functional association networks (Barabasi and Oltvai, 2004; Girvan and Newman, 2002; Tong et al., 2004; Balazsi et al., 2005). Applications based on network analysis have been proven useful in areas such as predicting protein functions, identifying targets for structural genomics, facilitating drug discovery and design, and expe­ diting novel biomarker identification (Sharan et al., 2007; Chuang et al., 2007; Hopkins, 2008; Huang et al., 2008). In the first four sections of this chapter, we will review four types of commonly conducted network analyses on large-scale molecular networks and their applications: (1) Topology analysis focuses on the characterization of global network structures using quantitative measures, or network statistics. The applications of topology analysis include important node identification