NDLI: Alignment-Free Sequence Comparison over Hadoop for Computational Biology

Content Provider	IEEE Xplore Digital Library
Author	Cattaneo, G. Petrillo, U.F. Giancarlo, R. Roscigno, G.
Copyright Year	2015
Description	Author affiliation: Dipt. di Inf., Univ. degli Studi di Salerno, Fisciano, Italy (Cattaneo, G.; Roscigno, G.) \|\| Dipt. di Sci. Statistiche, Univ. di Roma “Sapienza”, Rome, Italy (Petrillo, U.F.) \|\| Dipt. di Mat. ed Inf., Univ. degli Studi di Palermo, Palermo, Italy (Giancarlo, R.)
Abstract	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.
Starting Page	184
Ending Page	192
File Size	269897
Page Count	9
File Format	PDF
ISBN	9781467375894
ISSN	15302016
DOI	10.1109/ICPPW.2015.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bioinformatics Computer architecture Biology Context Electronic mail Sequences Pattern matching Hadoop alignment-free sequence comparison and analysis distributed computing MapReduce
Content Type	Text
Resource Type	Article

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