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Network analysis of oncogenic Ras ac...

Stites, Edward Cooper.

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Network analysis of oncogenic Ras activation.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Network analysis of oncogenic Ras activation./
Author:	Stites, Edward Cooper.
Description:	156 p.
Notes:	Adviser: Kodi S. Ravichandran.
Contained By:	Dissertation Abstracts International68-11B.
Subject:	Biology, Molecular. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3289596
ISBN:	9780549322849

Network analysis of oncogenic Ras activation.
Stites, Edward Cooper.

Network analysis of oncogenic Ras activation. - 156 p.

Adviser: Kodi S. Ravichandran.

Thesis (Ph.D.)--University of Virginia, 2008.

The goal of this work was to use mathematical models to study biological cell signaling networks and use the structure of the network to mathematically predict biological behaviors, or the function, of the network. We have focused on the Ras signaling module as it has been very well studied, providing a well-accepted set of information regarding the network structure and the reactions between network components. Additionally, there are many important open questions in Ras biology where a mathematical model may be able to provide valuable insight.

ISBN: 9780549322849Subjects--Topical Terms:

1017719
Biology, Molecular.

Network analysis of oncogenic Ras activation.
LDR:02987nam 2200289 a 45 001 940583
005 20110518
008 110518s2008 ||||||||||||||||| ||eng d
020 $a 9780549322849
035 $a (UMI)AAI3289596
035 $a AAI3289596
040 $a UMI $c UMI
100 1 $a Stites, Edward Cooper. $3 1264715
245 1 0 $a Network analysis of oncogenic Ras activation.
300 $a 156 p.
500 $a Adviser: Kodi S. Ravichandran.
500 $a Source: Dissertation Abstracts International, Volume: 68-11, Section: B, page: 7130.
502 $a Thesis (Ph.D.)--University of Virginia, 2008.
520 $a The goal of this work was to use mathematical models to study biological cell signaling networks and use the structure of the network to mathematically predict biological behaviors, or the function, of the network. We have focused on the Ras signaling module as it has been very well studied, providing a well-accepted set of information regarding the network structure and the reactions between network components. Additionally, there are many important open questions in Ras biology where a mathematical model may be able to provide valuable insight.
520 $a To investigate the unregulated Ras activation associated with cancer, we developed and validated a mathematical model of Ras signaling. The quantitative similarities between model predictions and experimental data helped us conclude that the model may be a useful tool for investigating biological questions. Subsequent model-based predictions and associated experiments help explain how or why only one of two classes of activating Ras point mutations with in vitro transformation potential is commonly found in cancers. Subsequent experiments found patterns of Ras pathway activation consistent with model predictions for both mutant classes, suggesting that the model insight could indeed be correct. Although oncogenic Ras mutant biochemistry has been extensively studied experimentally, the model uncovers a novel, systems-level process that contributes to total Ras activation in cells harboring oncogenic Ras mutants. This predicted behavior is also supported by our experimental observations comparing RasGTP levels in cancer cell lines with and without spontaneous Ras mutations. We next addressed the ability of our model to test pharmaceutical strategies in silico. Since a nonlinear dynamical system can have different behaviors for different sets of network parameters, we asked whether a drug could cause stronger inhibition on the cancerous Ras network than on the wild-type network. We identify such a strategy. Taken together, the system-level analysis of the oncogenic Ras network provides new insights and potential therapeutic strategies.
590 $a School code: 0246.
650 4 $a Biology, Molecular. $3 1017719
650 4 $a Biophysics, General. $3 1019105
690 $a 0307
690 $a 0786
710 2 $a University of Virginia. $3 645578
773 0 $t Dissertation Abstracts International $g 68-11B.
790 $a 0246
790 1 0 $a Ravichandran, Kodi S., $e advisor
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3289596