Network analysis for exploring systems biology

Life is one of the most complex phenomena in the universe. To understand complex biological systems, it requires the integration of experimental and computational research - in other words a systems biology approach. Many theoretical methods and models exist for exploring systems biology including well-known examples such as statistical inference, graph analysis, network inference, and dynamic modeling. These systems play a key role in the development of systems biology. The trend in the development of these methods and models gives an integrative framework to acquire a global perspective beyond the traditional reductionistic views of molecular biology. We will here present our review which specifically focuses on network theory to analyze systems biology with two goals in mind: to aid researchers in efficiently understanding the network theory for systems biology analysis; and to illustrate the necessary and realistic goals how complex networks can be integrated into systems biology research.