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Bayesian hierarchical models in char...

Datta, Saheli.

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Bayesian hierarchical models in characterizing molecular adaptation.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Bayesian hierarchical models in characterizing molecular adaptation./
Author:	Datta, Saheli.
Description:	161 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .
Contained By:	Dissertation Abstracts International72-07B.
Subject:	Biology, Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3452533
ISBN:	9781124603865

Bayesian hierarchical models in characterizing molecular adaptation.
Datta, Saheli.

Bayesian hierarchical models in characterizing molecular adaptation. - 161 p.

Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .

Thesis (Ph.D.)--University of California, Santa Cruz, 2011.

Assessing the selective influence of amino acid properties is important in understanding evolution at the molecular level. A collection of methods and models have been developed in recent years to determine if amino acid sites in a given DNA sequence alignment display substitutions that are altering or conserving a pre-specified set of amino acid properties. Residues showing an increased number of substitutions that favorably alter a physicochemical property are considered targets of positive natural selection. Such approaches usually perform independent analyses for each amino acid property under consideration, without taking into account the fact that some of the properties may be highly correlated.

ISBN: 9781124603865Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Bayesian hierarchical models in characterizing molecular adaptation.
LDR:02273nam 2200301 4500 001 1403064
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008 130515s2011 ||||||||||||||||| ||eng d
020 $a 9781124603865
035 $a (UMI)AAI3452533
035 $a AAI3452533
040 $a UMI $c UMI
100 1 $a Datta, Saheli. $3 1682303
245 1 0 $a Bayesian hierarchical models in characterizing molecular adaptation.
300 $a 161 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .
500 $a Adviser: Raquel Prado.
502 $a Thesis (Ph.D.)--University of California, Santa Cruz, 2011.
520 $a Assessing the selective influence of amino acid properties is important in understanding evolution at the molecular level. A collection of methods and models have been developed in recent years to determine if amino acid sites in a given DNA sequence alignment display substitutions that are altering or conserving a pre-specified set of amino acid properties. Residues showing an increased number of substitutions that favorably alter a physicochemical property are considered targets of positive natural selection. Such approaches usually perform independent analyses for each amino acid property under consideration, without taking into account the fact that some of the properties may be highly correlated.
520 $a We propose a suite of Bayesian hierarchical regression models that allow us to determine which sites display substitutions that conserve or radically change a set of amino acid properties. The proposed models take into account correlations that may be present in the data, both at the level of sites and properties. The models also properly adjust for multiple comparisons. We illustrate our approaches by analyzing simulated data sets and real data examples. Our analyses indicate that a more complete quantitative and qualitative characterization of molecular adaptation is achieved by taking into account changes in amino acid properties.
590 $a School code: 0036.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Statistics. $3 517247
650 4 $a Biology, Bioinformatics. $3 1018415
690 $a 0308
690 $a 0463
690 $a 0715
710 2 $a University of California, Santa Cruz. $3 1018764
773 0 $t Dissertation Abstracts International $g 72-07B.
790 1 0 $a Prado, Raquel, $e advisor
790 $a 0036
791 $a Ph.D.
792 $a 2011
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3452533