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Clustering sequences using mixture t...

Chen, Shu-Chuan.

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Clustering sequences using mixture trees.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Clustering sequences using mixture trees./
Author:	Chen, Shu-Chuan.
Description:	127 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3350.
Contained By:	Dissertation Abstracts International64-07B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3096944

Clustering sequences using mixture trees.
Chen, Shu-Chuan.

Clustering sequences using mixture trees. - 127 p.

Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3350.

Thesis (Ph.D.)--The Pennsylvania State University, 2003.

In this thesis, an ancestral mixture model for clustering discrete multivariate data is proposed. This model has a natural relationship to the coalescent process of population genetics. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By sliding the sieve parameter, one can create a hierarchical tree that estimates the population structure at each fixed backward point in time.Subjects--Topical Terms:

517247
Statistics.

Clustering sequences using mixture trees.
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035 $a (UnM)AAI3096944
035 $a AAI3096944
040 $a UnM $c UnM
100 1 $a Chen, Shu-Chuan. $3 1946636
245 1 0 $a Clustering sequences using mixture trees.
300 $a 127 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3350.
500 $a Adviser: Bruce G. Lindsay.
502 $a Thesis (Ph.D.)--The Pennsylvania State University, 2003.
520 $a In this thesis, an ancestral mixture model for clustering discrete multivariate data is proposed. This model has a natural relationship to the coalescent process of population genetics. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By sliding the sieve parameter, one can create a hierarchical tree that estimates the population structure at each fixed backward point in time.
520 $a A preliminary computer study of clustering the mtDNA sequences of Griffiths et al. (1994) indicates our approach performs well. The author also further develop some theoretical and computational properties of the ancestral mixture model. A quadratic distance based model selection for goodness of fit is proposed. In addition, some potential applications including haplotype reconstruction, estimating the human nucleotide diversity from shotgun sequencing data, and comparing case and control groups in disease studies are discussed. It is believed the ancestral mixture model could be a simple powerful tool in these studies.
590 $a School code: 0176.
650 4 $a Statistics. $3 517247
650 4 $a Biology, Biostatistics. $3 1018416
690 $a 0463
690 $a 0308
710 2 0 $a The Pennsylvania State University. $3 699896
773 0 $t Dissertation Abstracts International $g 64-07B.
790 1 0 $a Lindsay, Bruce G., $e advisor
790 $a 0176
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3096944