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Dissecting pathways with the yeast k...

Peyser, Brian D.

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Dissecting pathways with the yeast knockout collection.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Dissecting pathways with the yeast knockout collection./
Author:	Peyser, Brian D.
Description:	230 p.
Notes:	Adviser: Forrest A. Spencer.
Contained By:	Dissertation Abstracts International68-05B.
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3267880
ISBN:	9780549064107

Dissecting pathways with the yeast knockout collection.
Peyser, Brian D.

Dissecting pathways with the yeast knockout collection. - 230 p.

Adviser: Forrest A. Spencer.

Thesis (Ph.D.)--The Johns Hopkins University, 2007.

The yeast knockout collections provide opportunities to perform massively parallel phenotyping of deletion mutants for almost every yeast open reading frame. I used the knockout collection to screen for synthetic lethal partners, defined as alleles that cause lethality when combined but are nonlethal alone, with CTF4 and CTF18 and present the results in Chapter 2. I developed procedures for interpreting microarrays designed to compare changes in oligonucleotide TAGs specific to each knockout strain and present those methods in Chapters 3 and 4. These TAG microarrays allow thousands of experiments to screen for synthetic lethality among pairs of null alleles to be accomplished relatively quickly. In Chapter 4, I present 1410 novel predicted synthetic lethal interactions based on 707 currently completed screens. Interpretation of synthetic lethality is presented with a computational approach in Chapter 5, termed the congruence score. High congruence scores associate genes into common pathways, and I use the method to predict that YLL049W is a component of the dynein-dynactin nuclear orientation pathway. In Chapter 6, I propose a generalization of the congruence score to any phenotype, such as growth rate in the presence of various compounds, or even non-quantitative phenotypes such as cell morphology. This procedure connects genes based on similarity of multiple phenotypes using an application of information theory to produce a shared information score. Using gene ontology similarity, I show that high scores are associated with similarly annotated genes.

ISBN: 9780549064107Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Dissecting pathways with the yeast knockout collection.
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020 $a 9780549064107
035 $a (UMI)AAI3267880
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040 $a UMI $c UMI
100 1 $a Peyser, Brian D. $3 1271079
245 1 0 $a Dissecting pathways with the yeast knockout collection.
300 $a 230 p.
500 $a Adviser: Forrest A. Spencer.
500 $a Source: Dissertation Abstracts International, Volume: 68-05, Section: B, page: 2743.
502 $a Thesis (Ph.D.)--The Johns Hopkins University, 2007.
520 $a The yeast knockout collections provide opportunities to perform massively parallel phenotyping of deletion mutants for almost every yeast open reading frame. I used the knockout collection to screen for synthetic lethal partners, defined as alleles that cause lethality when combined but are nonlethal alone, with CTF4 and CTF18 and present the results in Chapter 2. I developed procedures for interpreting microarrays designed to compare changes in oligonucleotide TAGs specific to each knockout strain and present those methods in Chapters 3 and 4. These TAG microarrays allow thousands of experiments to screen for synthetic lethality among pairs of null alleles to be accomplished relatively quickly. In Chapter 4, I present 1410 novel predicted synthetic lethal interactions based on 707 currently completed screens. Interpretation of synthetic lethality is presented with a computational approach in Chapter 5, termed the congruence score. High congruence scores associate genes into common pathways, and I use the method to predict that YLL049W is a component of the dynein-dynactin nuclear orientation pathway. In Chapter 6, I propose a generalization of the congruence score to any phenotype, such as growth rate in the presence of various compounds, or even non-quantitative phenotypes such as cell morphology. This procedure connects genes based on similarity of multiple phenotypes using an application of information theory to produce a shared information score. Using gene ontology similarity, I show that high scores are associated with similarly annotated genes.
590 $a School code: 0098.
650 4 $a Biology, Bioinformatics. $3 1018415
690 $a 0715
710 2 $a The Johns Hopkins University. $3 1017431
773 0 $t Dissertation Abstracts International $g 68-05B.
790 $a 0098
790 1 0 $a Spencer, Forrest A., $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3267880