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Discovery and analysis of mosaic arr...

Zhi, Degui.

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Discovery and analysis of mosaic arrangements in biological sequences and structures.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Discovery and analysis of mosaic arrangements in biological sequences and structures./
Author:	Zhi, Degui.
Description:	173 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5219.
Contained By:	Dissertation Abstracts International66-10B.
Subject:	Biology, Genetics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3194816
ISBN:	9780542384646

Discovery and analysis of mosaic arrangements in biological sequences and structures.
Zhi, Degui.

Discovery and analysis of mosaic arrangements in biological sequences and structures. - 173 p.

Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5219.

Thesis (Ph.D.)--University of California, San Diego, 2006.

Biological molecules are composed of discrete units, called domains. The study of the identity and organization of these domains can reveal the correspondence between individual units in different molecules, and the history of domains themselves, which may guide our understanding of the evolutionary history of individual molecules. Currently, the study of domain organization in protein sequences is a mature field; however, the studies of domain organization in other types of biological sequences and protein structures are still in their infancy. There is currently no general framework and specific tools for the identification of domains or for the discovery of the domain organization.

ISBN: 9780542384646Subjects--Topical Terms:

1017730
Biology, Genetics.

Discovery and analysis of mosaic arrangements in biological sequences and structures.
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100 1 $a Zhi, Degui. $3 1914399
245 1 0 $a Discovery and analysis of mosaic arrangements in biological sequences and structures.
300 $a 173 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5219.
500 $a Chair: Pavel Pevzner.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2006.
520 $a Biological molecules are composed of discrete units, called domains. The study of the identity and organization of these domains can reveal the correspondence between individual units in different molecules, and the history of domains themselves, which may guide our understanding of the evolutionary history of individual molecules. Currently, the study of domain organization in protein sequences is a mature field; however, the studies of domain organization in other types of biological sequences and protein structures are still in their infancy. There is currently no general framework and specific tools for the identification of domains or for the discovery of the domain organization.
520 $a Existing tools do not explicitly define what a domain is. In some cases, existing tools (e.g., multiple sequence alignment tools) ignore domain organizations entirely, or represent only a limited subset of domain organization. As a result, the mosaic structures of biological data are left undetected, and we demonstrate that the prevalence of mosaic arrangements is under-appreciated.
520 $a This dissertation considers shortcomings of current technologies and develops a generic framework for the discovery and analysis of domain organizations in any types of sequential data. We apply this framework in several biological contexts. First we develop the A-Bruijn Aligner (ABA), which represents a multiple sequence alignment (MSA) as a graph that automatically reveals the domain structures. Second, we develop a repeat domain graph approach that decomposes a repeat family library into repeat domains, which is the first method for the comprehensive identification of repeat domains in large genomes. Third, we extend the A-Bruijn graph approach to an exploration of the mosaic arrangements in protein structures. Finally, we propose a new method for structure comparison based on a simplified representation of protein structures using the local curvatures along their generalized backbones.
590 $a School code: 0033.
650 4 $a Biology, Genetics. $3 1017730
650 4 $a Computer Science. $3 626642
690 $a 0369
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710 2 0 $a University of California, San Diego. $3 1018093
773 0 $t Dissertation Abstracts International $g 66-10B.
790 1 0 $a Pevzner, Pavel, $e advisor
790 $a 0033
791 $a Ph.D.
792 $a 2006
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