(untitled) (Journal of Fiber Bioengineering and Informatics, 2015)
Detecting protein complexes from Protein-protein Interaction (PPI) networks has been the focus of many recent efforts on protein. With the appearance of big data and large scale PPI networks, traditional sequential methods, which analyze interaction networks and detect protein complexes, do not utilize high performance computing. In this paper, we propose a parallel algorithm using cloud computing method to improve the computational efficiency and detect protein complexes. Because MapReduce programming model simplifies the implementation of many data parallel applications, firstly we use it to calculate the value of each edge and the value of each node from PPI networks, then expand complexes. At last, we perform the algorithm on different data to test the speedup of the algorithm. Moreover, through the parallel algorithm is compared with sequential method, experimental results show that the running time of parallel algorithm is short. We get a conclusion that parallel algorithm can also accurately assign proteins with similar functions to a complex.