Most of current methods mainly focus on topological information and fail to consider the information from protein primary sequence which is of considerable importance for protein complex detection. Based on this observation, we propose a novel algorithm called CDIP (Complex Detection based on Integrated Properties) to discover protein complexes from the yeast PPI network. In our method, a simple feature representation from protein primary sequence is presented and become a novel part of feature properties. The algorithm can consider both topological and biological information (amino acid background frequency), which is helpful to detect protein complex more efficiently. The experiments conducted on two public datasets show that the proposed algorithm outperforms the two state-of-the-art protein complex detection algorithms. © 2011 Springer-Verlag.
CITATION STYLE
Yu, Y., Lin, L., Sun, C., Wang, X., & Wang, X. (2011). Complex detection based on integrated properties. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7062 LNCS, pp. 121–128). https://doi.org/10.1007/978-3-642-24955-6_15
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