東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Microarray-based genomic mapping.

West, Joseph Alfred.

Linked to FindBook

Google Book

Amazon

博客來

Microarray-based genomic mapping.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Microarray-based genomic mapping./
Author:	West, Joseph Alfred.
Description:	90 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3114.
Contained By:	Dissertation Abstracts International64-07B.
Subject:	Biology, Molecular. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3098798

Microarray-based genomic mapping.
West, Joseph Alfred.

Microarray-based genomic mapping. - 90 p.

Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3114.

Thesis (Ph.D.)--State University of New York at Stony Brook, 2003.

Micro-arrays are an ideal tool for high resolution mapping of complex genomes because, in principle, a large amount of data can be collected in parallel from a single experiment. We have developed a method that uses micro-array hybridization and representation technologies to order sets of unique probes derived from any genome of interest. We will describe a procedure for identifying a type of unique probe based on representational technologies, and a technique for clustering the probes into large linear contigs using hybridization data from micro-arrays. The method will utilize arrays, hybridization, genome sampling techniques and algorithmic analyses to determine the relative order of the probes along the genome. The order of the arrayed probes can be deduced from a series of hybridizations to the arrays using labeled random pools of clones from the target genome. The conceptual foundation of the technique is based on the observation that probe proximity can be inferred by analysis of the hybridization signals of all probes over the hybridization series. A proximity metric based upon the Hamming distance is calculated for all pair wise combination of probes, and these distances are then used as input for a contig assembly algorithm. We show that the Hamming distance metric is particularly appropriate for this application and that our clustering algorithm produces well ordered large probe contigs using this metric. Finally we discuss possible extensions of the technique and applications to the fields of evolutionary biology, comparative genomics, and medical genetics.Subjects--Topical Terms:

1017719
Biology, Molecular.

Microarray-based genomic mapping.
LDR:02450nmm 2200277 4500 001 1858373
005 20040927073708.5
008 130614s2003 eng d
035 $a (UnM)AAI3098798
035 $a AAI3098798
040 $a UnM $c UnM
100 1 $a West, Joseph Alfred. $3 1946065
245 1 0 $a Microarray-based genomic mapping.
300 $a 90 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3114.
500 $a Adviser: Michael Wigler.
502 $a Thesis (Ph.D.)--State University of New York at Stony Brook, 2003.
520 $a Micro-arrays are an ideal tool for high resolution mapping of complex genomes because, in principle, a large amount of data can be collected in parallel from a single experiment. We have developed a method that uses micro-array hybridization and representation technologies to order sets of unique probes derived from any genome of interest. We will describe a procedure for identifying a type of unique probe based on representational technologies, and a technique for clustering the probes into large linear contigs using hybridization data from micro-arrays. The method will utilize arrays, hybridization, genome sampling techniques and algorithmic analyses to determine the relative order of the probes along the genome. The order of the arrayed probes can be deduced from a series of hybridizations to the arrays using labeled random pools of clones from the target genome. The conceptual foundation of the technique is based on the observation that probe proximity can be inferred by analysis of the hybridization signals of all probes over the hybridization series. A proximity metric based upon the Hamming distance is calculated for all pair wise combination of probes, and these distances are then used as input for a contig assembly algorithm. We show that the Hamming distance metric is particularly appropriate for this application and that our clustering algorithm produces well ordered large probe contigs using this metric. Finally we discuss possible extensions of the technique and applications to the fields of evolutionary biology, comparative genomics, and medical genetics.
590 $a School code: 0771.
650 4 $a Biology, Molecular. $3 1017719
650 4 $a Chemistry, Biochemistry. $3 1017722
650 4 $a Biology, Genetics. $3 1017730
690 $a 0307
690 $a 0487
690 $a 0369
710 2 0 $a State University of New York at Stony Brook. $3 1019194
773 0 $t Dissertation Abstracts International $g 64-07B.
790 1 0 $a Wigler, Michael, $e advisor
790 $a 0771
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3098798