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The recognition of essential proteins not only can help to understand themechanism of cell operation, but also help to study the mechanism of biologicalevolution. At present, many scholars have been discovering essential proteinsaccording to the topological structure of protein network and complexes. Whilesome proteins still can not be recognized. In this paper, we proposed two newmethods complex degree centrality (CDC) and complex in-degree and betweennessdefinition (CIBD) which integrate the local character of protein complexes andtopological properties to determine the essentiality of proteins. First, wegive the definitions of complex average centrality (CAC) and complex hybridcentrality (CHC) which both describe the properties of protein complexes. Thenwe propose these new methods CDC and CIBD based on CAC and CHC definitions. Inorder to access these two methods, different Protein-Protein Interaction (PPI)networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used asexperimental materials. Experimental results in networks show that the methodsof CDC and CIBD can help to improve the precision of predicting essentialproteins.

Two new methods for identifying proteins based on the domain protein complexes and topological properties