Complex network analysis has received increasing interest in recent years, which provides a remarkable tool to describe complex systems of interacting entities, particular for biological systems. In this paper, we propose a methodology for identifying the significant nodes of the networks, including core nodes, bridge nodes and high-influential nodes, based on the idea of community and two new ranking measures, InterRank and IntraRank. The results show the significant nodes form a small number in biological networks, and uncover the relative small number of which has advantage for reducing the dimensions of the network and possibly help to define new biological targets.