Abstract
Identification of protein complexes from protein-protein interaction network has become a key problem for understanding cellular life in post-genomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. Not only is the topological characters but also dynamic meaning considered in DPC. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. According to core-attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense sub-graphs. All possible protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness”. Others which not belong to always active proteins are considered as potential attachments. On a certain time course, an attachment protein can only participate in one protein complex. Based on this idea, we first find a best protein-complex core for each potential attachment. It means that if a protein would be actived at the some time, it would be added into the best protein-complex core for forming protein complexes. According to the formation and function of a protein complex, it should be active in two or more continual time courses. Based on the above analysis, we use the following rules to filter false positive complexes: 1) A protein complex should include at least two proteins; 2) The attachment proteins should be active in the same time course or in different but adjacent time courses; 3) If the attachments of a possible protein complex do not satisfy the second rule and the protein-complex core involves at least two proteins, the core will be kept as a final protein complex. So final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Scaccharomves cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH and Core-Attachment based on the validation of matching with known complexes and hF-measures.