@Article{JFBI-8-3,
author = {},
title = {A Parallel Algorithm for Detecting Complexes in Protein-protein Interaction Networks with MapReduce},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2015},
volume = {8},
number = {3},
pages = {565--574},
abstract = {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.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbim00123},
url = {https://global-sci.com/article/86599/a-parallel-algorithm-for-detecting-complexes-in-protein-protein-interaction-networks-with-mapreduce}
}