國立虎尾科技大學 |

Combinatorial Algorithms for Haplotype Assembly.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Combinatorial Algorithms for Haplotype Assembly./
作者:	Mazrouee, Sepideh.
面頁冊數:	1 online resource (170 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.
Contained By:	Dissertation Abstracts International79-04B(E).
標題:	Conservation biology. -
電子資源:	click for full text (PQDT)
ISBN:	9780355396348

Combinatorial Algorithms for Haplotype Assembly.
Mazrouee, Sepideh.

Combinatorial Algorithms for Haplotype Assembly. - 1 online resource (170 pages)

Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Many phenotypes such as genetic disorders may be hereditary while others may be influenced by the environment. However, some genetic disorders are due to new mutations in the individuals DeoxyriboNucleic Acid (DNA). Diseases such as diabetes and specific types of cancer are examples of the conditions that can be inherited or affected by lifestyle genetic mutations. In order to investigate and predict the incidence of such diseases, sequences of single individuals need to be examined. In the past decade, the Next Generation Sequencing (NGS) technology has enabled us to generate DNA sequences of many organisms. Yet, reconstructing each copy of chromosome remains an open research problem due to computational challenges associated with processing a massive amount of DNA data and understanding complex structure of such data for individual DNA phasing.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355396348Subjects--Topical Terms:

579656
Conservation biology.
Index Terms--Genre/Form:

554714
Electronic books.

Combinatorial Algorithms for Haplotype Assembly.
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245 1 0 $a Combinatorial Algorithms for Haplotype Assembly.
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300 $a 1 online resource (170 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.
500 $a Adviser: Wei -. Wang.
502 $a Thesis (Ph.D.) $c University of California, Los Angeles $d 2017.
504 $a Includes bibliographical references
520 $a Many phenotypes such as genetic disorders may be hereditary while others may be influenced by the environment. However, some genetic disorders are due to new mutations in the individuals DeoxyriboNucleic Acid (DNA). Diseases such as diabetes and specific types of cancer are examples of the conditions that can be inherited or affected by lifestyle genetic mutations. In order to investigate and predict the incidence of such diseases, sequences of single individuals need to be examined. In the past decade, the Next Generation Sequencing (NGS) technology has enabled us to generate DNA sequences of many organisms. Yet, reconstructing each copy of chromosome remains an open research problem due to computational challenges associated with processing a massive amount of DNA data and understanding complex structure of such data for individual DNA phasing.
520 $a In this dissertation, I introduce several computational frameworks for understanding the complex structure of DNA sequence data to reconstruct chromosome copies in diploid and polyploid organisms. The methodologies that are presented in this dissertation span several areas of research including unsupervised learning, combinatorial optimization, graph partitioning, and association rule learning. The overarching theme of this research is design and validation of novel combinatorial algorithms for fast and accurate haplotype assembly. The first two frameworks presented in this dissertation, called FastHap and ARHap, are tailored toward providing computationally simple diploid haplotypes with the objective of minimizing minimum error correction and switching error, respectively. I then introduce HapColor and PolyCluster, which aim to improve minimum error correction and switching error in polyploid haplotyping.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Conservation biology. $3 579656
650 4 $a Bioinformatics. $3 583857
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
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690 $a 0715
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710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Los Angeles. $b Computer Science. $3 1180947
773 0 $t Dissertation Abstracts International $g 79-04B(E).
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