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

Modeling and analysis of the Escheri...

Joyce, Andrew Robert.

Linked to FindBook

Google Book

Amazon

博客來

Modeling and analysis of the Escherichia coli transcriptional regulatory network: An assessment of its properties, plasticity, and role in adaptive evolution.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Modeling and analysis of the Escherichia coli transcriptional regulatory network: An assessment of its properties, plasticity, and role in adaptive evolution./
Author:	Joyce, Andrew Robert.
Description:	274 p.
Notes:	Advisers: Bernhard O. Palsson; Bing Ren.
Contained By:	Dissertation Abstracts International68-06B.
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3272676
ISBN:	9780549120308

Modeling and analysis of the Escherichia coli transcriptional regulatory network: An assessment of its properties, plasticity, and role in adaptive evolution.
Joyce, Andrew Robert.

Modeling and analysis of the Escherichia coli transcriptional regulatory network: An assessment of its properties, plasticity, and role in adaptive evolution. - 274 p.

Advisers: Bernhard O. Palsson; Bing Ren.

Thesis (Ph.D.)--University of California, San Diego, 2007.

The emergence of whole-genome sequencing and other high-throughput experimental technologies in recent years has transformed life sciences research from a relatively data-poor discipline into one that is data-rich. Studies of transcriptional regulatory networks, in particular, have benefited from these developments as high throughput post-genomic data yield system-wide measurements that reveal the components, interactions, and functional states of regulatory systems in response to environmental stimuli.

ISBN: 9780549120308Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Modeling and analysis of the Escherichia coli transcriptional regulatory network: An assessment of its properties, plasticity, and role in adaptive evolution.
LDR:03616nam 2200349 a 45 001 947641
005 20110524
008 110524s2007 ||||||||||||||||| ||eng d
020 $a 9780549120308
035 $a (UMI)AAI3272676
035 $a AAI3272676
040 $a UMI $c UMI
100 1 $a Joyce, Andrew Robert. $3 1271110
245 1 0 $a Modeling and analysis of the Escherichia coli transcriptional regulatory network: An assessment of its properties, plasticity, and role in adaptive evolution.
300 $a 274 p.
500 $a Advisers: Bernhard O. Palsson; Bing Ren.
500 $a Source: Dissertation Abstracts International, Volume: 68-06, Section: B, page: 3482.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2007.
520 $a The emergence of whole-genome sequencing and other high-throughput experimental technologies in recent years has transformed life sciences research from a relatively data-poor discipline into one that is data-rich. Studies of transcriptional regulatory networks, in particular, have benefited from these developments as high throughput post-genomic data yield system-wide measurements that reveal the components, interactions, and functional states of regulatory systems in response to environmental stimuli.
520 $a Accordingly, the analysis of transcriptional regulatory networks is the primary topic of this dissertation. To this end, there are dual focal points; the first involves the static modeling of transcriptional regulatory networks, and the second studies how they change during adaptive evolution. The former activity centers on developing a novel approach, called the R matrix formalism, for modeling transcriptional regulatory networks, first, in small model systems, and then by applying the methodology to Escherichia coli. In contrast, the latter activity focuses on investigating how E. coli adapts to environmental perturbations, namely growth on the relatively poor substrates glycerol- and L-lactate-minimal medium, in the laboratory using various post-genomic and traditional experimental techniques.
520 $a The results presented herein constitute significant advances on several fronts. First, the R-matrix framework for modeling transcriptional regulatory networks, while largely proof-of-concept in the context of this dissertation, will likely prove useful as an integrative method for compiling and analyzing the rapidly growing body of ChIP-chip and transcriptional profiling data, in addition to providing a novel means to study other systems and pathways.
520 $a Furthermore, the adaptive evolution work highlights the striking malleability of the transcriptional regulatory network when faced with environmental perturbations. Specifically, the RNA polymerase is directly mutated in the glycerol-adaptation experiments, whereas cAMP- and ppGpp-related pathways are targeted in the L-lactate case. Therefore, when taken together, this dissertation provides a novel approach to modeling regulatory networks as static entities, while additionally providing an unprecedented view into the dynamic nature of these networks during adaptation and the critical role that they play in determining the cellular phenotype.
590 $a School code: 0033.
650 4 $a Biology, Bioinformatics. $3 1018415
690 $a 0715
710 2 $a University of California, San Diego. $b Bioinformatics. $3 1025305
773 0 $t Dissertation Abstracts International $g 68-06B.
790 $a 0033
790 1 0 $a Chao, Lin $e committee member
790 1 0 $a Palsson, Bernhard O., $e advisor
790 1 0 $a Ren, Bing, $e advisor
790 1 0 $a Saier, Milton $e committee member
790 1 0 $a Wang, Wei $e committee member
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3272676