Efficient protein structure alignment algorithms under the MapReduce framework

Currently, cloud computing has been applied to share computing resources to achieve coherence and economies of scale similar to a utility over a network. Hadoop is an widely-used open-source cloud computing environment that implements the Google MapReduce framework. Many bioinformatics tools have been developed to provide cloud services by using Hadoop. This paper proposes approaches in providing a pairwise 3D protein structure alignment; our web service takes advantage of the MapReduce paradigm as means of management and parallelizing tools under massive number of protein pairs examined under the experiment. It shows that our previously proposed sequential combinatorial algorithms are well parallelized under the map/reduce platform. These methods are tested on the real-world data obtained in from the RCSB PDB data set; the computation efficiency can be effectively improved proportional to the number of processors being used.