東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Highly scalable short read alignment...

University of Maryland, College Park., Computer Science.

FindBook

Google Book

Amazon

博客來

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

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Highly scalable short read alignment with the Burrows-Wheeler transform and cloud computing./
作者:	Langmead, Benjamin Thomas.
面頁冊數:	76 p.
附註:	Advisers: Steven L. Salzberg; Mihai Pop.
Contained By:	Masters Abstracts International48-01.
標題:	Biology, Bioinformatics. -
電子資源:	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.
LDR:02045nam 2200337 a 45 001 853187
005 20100701
008 100701s2009 ||||||||||||||||| ||eng d
020 $a 9781109381511
035 $a (UMI)AAI1469418
035 $a AAI1469418
040 $a UMI $c UMI
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
690 $a 0369
690 $a 0715
690 $a 0984
710 2 $a University of Maryland, College Park. $b Computer Science. $3 1018451
773 0 $t Masters Abstracts International $g 48-01.
790 $a 0117
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
791 $a M.S.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1469418