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Experimental design and the detectio...

State University of New York at Albany.

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Experimental design and the detection of adaptive molecular divergence in phylogenetics and genomics.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Experimental design and the detection of adaptive molecular divergence in phylogenetics and genomics./
作者:	de Koning, A. P. Jason.
面頁冊數:	207 p.
附註:	Source: Dissertation Abstracts International, Volume: 68-12, Section: B, page: 7742.
Contained By:	Dissertation Abstracts International68-12B.
標題:	Biology, Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3293137
ISBN:	9780549369134

Experimental design and the detection of adaptive molecular divergence in phylogenetics and genomics.
de Koning, A. P. Jason.

Experimental design and the detection of adaptive molecular divergence in phylogenetics and genomics. - 207 p.

Source: Dissertation Abstracts International, Volume: 68-12, Section: B, page: 7742.

Thesis (Ph.D.)--State University of New York at Albany, 2007.

The limitations of widely-used methods for inferring the action of natural selection at the molecular level have been largely ignored to date. The focus of this dissertation has been to explore when methods for detecting positive selection perform poorly, and to improve their limits of resolution. This work has been particularly concerned with improving inferences made on short lineages - such as the human and chimpanzee lineages since diverging from a common ancestor - so as to improve the detection of brief 'adaptive bursts'.

ISBN: 9780549369134Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Experimental design and the detection of adaptive molecular divergence in phylogenetics and genomics.
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245 1 0 $a Experimental design and the detection of adaptive molecular divergence in phylogenetics and genomics.
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500 $a Source: Dissertation Abstracts International, Volume: 68-12, Section: B, page: 7742.
502 $a Thesis (Ph.D.)--State University of New York at Albany, 2007.
520 $a The limitations of widely-used methods for inferring the action of natural selection at the molecular level have been largely ignored to date. The focus of this dissertation has been to explore when methods for detecting positive selection perform poorly, and to improve their limits of resolution. This work has been particularly concerned with improving inferences made on short lineages - such as the human and chimpanzee lineages since diverging from a common ancestor - so as to improve the detection of brief 'adaptive bursts'.
520 $a Taken together, the results presented in this thesis suggest that: (1) existing approaches for detecting selection using individual genes to estimate the ratio of non-synonymous to synonymous divergence (dN/d S) are often unable to distinguish positive selection from neutral evolution on short lineages; (2) problems arise when analyzing short lineages because individual genes often contain too little information to allow precise estimation of the neutral rate; (3) novel experimental designs that allow the neutral rate to be estimated over multiple genes or regions lead to dramatic improvements in estimates of dN/d S and in the power to detect selection, without increasing false positives; and (4) application of these new experimental designs in conjunction with improved models can lead to significantly different conclusions about the forces that drove molecular divergence.
520 $a By using these methods on both primate lysozyme and phylogenomic datasets, I show that inferences made about positive selection along short lineages are more consistent with biological expectations than are inferences based on standard approaches. Using simulation, I further demonstrate that the methodological and experimental design factors addressed lead to improved accuracy, precision, and power. It is my hope that the improved methods and case studies presented here will stimulate greater appreciation for experimental design in phylogenetic and phylogenomic analysis. Toward this goal, I have developed novel asymptotic power approximation methods that should facilitate incorporation of fast and accurate a priori power analysis into experimental design. All methods developed for this dissertation are implemented in an accelerated maximum likelihood software package that I wrote ('PIDAMEBL'), which will be made freely available to the research community.
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