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Oxford University Press (OUP), Bioinformatics, 11(30), p. 1508-1513

DOI: 10.1093/bioinformatics/btu071

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Supercomputing for the parallelization of whole genome analysis

Journal article published in 2014 by Megan J. Puckelwartz, Lorenzo Ll Pesce, Viswateja Nelakuditi, Lisa Dellefave-Castillo, Jessica R. Golbus, Sharlene M. Day, Thomas P. Cappola, Gerald W. Dorn, Ian T. Foster, Elizabeth M. McNally ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Motivation: The declining cost of generating DNA sequence is promoting an increase in whole genome sequencing, especially as applied to the human genome. Whole genome analysis requires the alignment and comparison of raw sequence data, and results in a computational bottleneck because of limited ability to analyze multiple genomes simultaneously.