6533b854fe1ef96bd12adefe

RESEARCH PRODUCT

Alignment-Free Sequence Comparison over Hadoop for Computational Biology

Umberto Ferraro PetrilloGiuseppe CattaneoGianluca RoscignoRaffaele Giancarlo

subject

SpeedupTheoretical computer scienceSettore INF/01 - InformaticaComputer scienceAlignment-free sequence comparison and analysis; Distributed computing; Hadoop; MapReduce; Software; Mathematics (all); Hardware and ArchitectureSequence alignmentContext (language use)Computational biologyDNA sequencingDistributed computingTask (project management)Alignment-free sequence comparison and analysisHadoopHardware and ArchitectureMathematics (all)Relevance (information retrieval)MapReducePattern matchingAlignment-free sequence comparison and analysiSoftware

description

Sequence comparison i.e., The assessment of how similar two biological sequences are to each other, is a fundamental and routine task in Computational Biology and Bioinformatics. Classically, alignment methods are the de facto standard for such an assessment. In fact, considerable research efforts for the development of efficient algorithms, both on classic and parallel architectures, has been carried out in the past 50 years. Due to the growing amount of sequence data being produced, a new class of methods has emerged: Alignment-free methods. Research in this ares has become very intense in the past few years, stimulated by the advent of Next Generation Sequencing technologies, since those new methods are very appealing in terms of computational resources needed and biological relevance. Despite such an effort and in contrast with sequence alignment methods, no systematic investigation of how to take advantage of distributed architectures to speed up alignment-free methods, has taken place. We provide a contribution of that kind, by evaluating the possibility of using the Hadoop distributed framework to speed up the running times of these methods, compared to their original sequential formulation.

10.1109/icppw.2015.28http://hdl.handle.net/10447/201070