東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Studying the Evolution of Gene Regul...

Leng, Jing.

Linked to FindBook

Google Book

Amazon

博客來

Studying the Evolution of Gene Regulation Using Next-Generation Sequencing: Computational Methods and Data Integration.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Studying the Evolution of Gene Regulation Using Next-Generation Sequencing: Computational Methods and Data Integration./
Author:	Leng, Jing.
Description:	136 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
Contained By:	Dissertation Abstracts International75-09B(E).
Subject:	Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3580748
ISBN:	9781321054057

Studying the Evolution of Gene Regulation Using Next-Generation Sequencing: Computational Methods and Data Integration.
Leng, Jing.

Studying the Evolution of Gene Regulation Using Next-Generation Sequencing: Computational Methods and Data Integration. - 136 p.

Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.

Thesis (Ph.D.)--Yale University, 2014.

This item must not be sold to any third party vendors.

Recent advances in next-generation sequencing have created new opportunities, as well as challenges, to study various aspects of gene regulation and their roles during evolution. In this dissertation, I present my thesis work on developing computational methodologies and integrative data analyses for relevant sequencing applications, in order to better understand the evolution of gene regulation -- focusing on cis-regulation of gene transcription and on alternative splicing. On the topic of cis-regulation of gene expression, I describe a project in which we used ChIP-Seq to examine the evolution of promoter and enhancer activities in the embryonic limb tissues of human, rhesus and mouse. On the topic of alternative splicing, I first present a computational tool called IQSeq that quantifies isoform expression levels using RNA-Seq data, along with its applications, especially in C. elegans. I then describe another bioinformatics pipeline LESSeq, designed for comparative analysis of RNA-Seq data at local alternative splicing events, as well as its applications to two datasets relevant to human evolution. Finally, I investigate duplications, specifically pseudogenes and paralogs, in the highly divergent species of human, worm and fly, and utilized functional genomics data to study their evolution.

ISBN: 9781321054057Subjects--Topical Terms:

553671
Bioinformatics.

Studying the Evolution of Gene Regulation Using Next-Generation Sequencing: Computational Methods and Data Integration.
LDR:02393nmm a2200301 4500 001 2059777
005 20150827082954.5
008 170521s2014 ||||||||||||||||| ||eng d
020 $a 9781321054057
035 $a (MiAaPQ)AAI3580748
035 $a AAI3580748
040 $a MiAaPQ $c MiAaPQ
100 1 $a Leng, Jing. $3 1907841
245 1 0 $a Studying the Evolution of Gene Regulation Using Next-Generation Sequencing: Computational Methods and Data Integration.
300 $a 136 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
500 $a Advisers: Mark B. Gerstein; James P. Noonan.
502 $a Thesis (Ph.D.)--Yale University, 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Recent advances in next-generation sequencing have created new opportunities, as well as challenges, to study various aspects of gene regulation and their roles during evolution. In this dissertation, I present my thesis work on developing computational methodologies and integrative data analyses for relevant sequencing applications, in order to better understand the evolution of gene regulation -- focusing on cis-regulation of gene transcription and on alternative splicing. On the topic of cis-regulation of gene expression, I describe a project in which we used ChIP-Seq to examine the evolution of promoter and enhancer activities in the embryonic limb tissues of human, rhesus and mouse. On the topic of alternative splicing, I first present a computational tool called IQSeq that quantifies isoform expression levels using RNA-Seq data, along with its applications, especially in C. elegans. I then describe another bioinformatics pipeline LESSeq, designed for comparative analysis of RNA-Seq data at local alternative splicing events, as well as its applications to two datasets relevant to human evolution. Finally, I investigate duplications, specifically pseudogenes and paralogs, in the highly divergent species of human, worm and fly, and utilized functional genomics data to study their evolution.
590 $a School code: 0265.
650 4 $a Bioinformatics. $3 553671
650 4 $a Evolution & development. $3 3172418
690 $a 0715
690 $a 0412
710 2 $a Yale University. $3 515640
773 0 $t Dissertation Abstracts International $g 75-09B(E).
790 $a 0265
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3580748