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Highly scalable short read alignment...

University of Maryland, College Park., Computer Science.

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Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing./
Author:	Langmead, Benjamin Thomas.
Description:	76 p.
Notes:	Advisers: Steven L. Salzberg; Mihai Pop.
Contained By:	Masters Abstracts International48-01.
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1469418
ISBN:	9781109381511

Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing.
Langmead, Benjamin Thomas.

Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing. - 76 p.

Advisers: Steven L. Salzberg; Mihai Pop.

Thesis (M.S.)--University of Maryland, College Park, 2009.

Improvements in DNA sequencing have both broadened its utility and dramatically increased the size of sequencing datasets. Sequencing instruments are now used regularly as sources of high-resolution evidence for genotyping, methylation profiling, DNA-protein interaction mapping, and characterizing gene expression in the human genome and in other species. With existing methods, the computational cost of aligning short reads from the Illumina instrument to a mammalian genome can be very large: on the order of many CPU months for one human genotyping project. This thesis presents a novel application of the Burrows-Wheeler Transform that enables the alignment of short DNA sequences to mammalian genomes at a rate much faster than existing hashtable-based methods. The thesis also presents an extension of the technique that exploits the scalability of Cloud Computing to perform the equivalent of one human genotyping project in hours.

ISBN: 9781109381511Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing.
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100 1 $a Langmead, Benjamin Thomas. $3 1019403
245 1 0 $a Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing.
300 $a 76 p.
500 $a Advisers: Steven L. Salzberg; Mihai Pop.
500 $a Source: Masters Abstracts International, Volume: 48-01, page: .
502 $a Thesis (M.S.)--University of Maryland, College Park, 2009.
520 $a Improvements in DNA sequencing have both broadened its utility and dramatically increased the size of sequencing datasets. Sequencing instruments are now used regularly as sources of high-resolution evidence for genotyping, methylation profiling, DNA-protein interaction mapping, and characterizing gene expression in the human genome and in other species. With existing methods, the computational cost of aligning short reads from the Illumina instrument to a mammalian genome can be very large: on the order of many CPU months for one human genotyping project. This thesis presents a novel application of the Burrows-Wheeler Transform that enables the alignment of short DNA sequences to mammalian genomes at a rate much faster than existing hashtable-based methods. The thesis also presents an extension of the technique that exploits the scalability of Cloud Computing to perform the equivalent of one human genotyping project in hours.
590 $a School code: 0117.
650 4 $a Biology, Bioinformatics. $3 1018415
650 4 $a Biology, Genetics. $3 1017730
650 4 $a Computer Science. $3 626642
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710 2 $a University of Maryland, College Park. $b Computer Science. $3 1018451
773 0 $t Masters Abstracts International $g 48-01.
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790 1 0 $a Kingsford, Carl $e committee member
790 1 0 $a Pop, Mihai $e committee member
790 1 0 $a Pop, Mihai, $e advisor
790 1 0 $a Salzberg, Steven L. $e committee member
790 1 0 $a Salzberg, Steven L., $e advisor
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792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1469418