Ontology type: schema:Chapter
2016
AUTHORSEnzo Rucci , Carlos García , Guillermo Botella , Armando De Giusti , Marcelo Naiouf , Manuel Prieto-Matías
ABSTRACTSearching biological sequence database is a common and repeated task in bioinformatics and molecular biology. The Smith–Waterman algorithm is the most accurate method for this kind of search. Unfortunately, this algorithm is computationally demanding and the situation gets worse due to the exponential growth of biological data in the last years. For that reason, the scientific community has made great efforts to accelerate Smith–Waterman biological database searches in a wide variety of hardware platforms. We give a survey of the state-of-the-art in Smith–Waterman protein database search, focusing on four hardware architectures: central processing units, graphics processing units, field programmable gate arrays and Xeon Phi coprocessors. After briefly describing each hardware platform, we analyse temporal evolution, contributions, limitations and experimental work and the results of each implementation. Additionally, as energy efficiency is becoming more important every day, we also survey performance/power consumption works. Finally, we give our view on the future of Smith–Waterman protein searches considering next generations of hardware architectures and its upcoming technologies. More... »
PAGES197-223
Big Data Analytics in Genomics
ISBN
978-3-319-41278-8
978-3-319-41279-5
http://scigraph.springernature.com/pub.10.1007/978-3-319-41279-5_6
DOIhttp://dx.doi.org/10.1007/978-3-319-41279-5_6
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