Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death
In a multi-cellular organism, cells constantly receive signals on their internal condition and surrounding environment. In response to various signals, cells proliferate, move around or even undergo suicide. The signal-response is controlled by complex molecular machinery, understanding of which is...
Main Author: | |
---|---|
Other Authors: | |
Format: | Others |
Published: |
Virginia Tech
2014
|
Subjects: | |
Online Access: | http://hdl.handle.net/10919/29443 http://scholar.lib.vt.edu/theses/available/etd-11032008-114621/ |
id |
ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-29443 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-294432020-09-26T05:33:44Z Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death Zhang, Tongli Genetics, Bioinformatics, and Computational Biology Tyson, John J. Li, Liwu Mendes, Pedro J. P. Finkielstein, Carla V. Burns, John A. Brazhnik, Paul mathematical modeling systems biology apoptosis p53 NFkB In a multi-cellular organism, cells constantly receive signals on their internal condition and surrounding environment. In response to various signals, cells proliferate, move around or even undergo suicide. The signal-response is controlled by complex molecular machinery, understanding of which is an important goal of basic molecular biological research. Such understanding is also valuable for clinical application, since lethal diseases like cancer show maladaptive responses to growth-regulating signals. Because the multiple feedbacks in the molecular regulatory machinery obscure cause-effect relations, it is hard to understand these control systems by intuition alone. Here we translate the molecular interactions into differential equations and recapture the cellular physiological properties with the help of numerical simulations and non-linear dynamical tools. The models address the physiological features of programmed cell death, the cell fate decision by p53 and the dynamics of the NF-?B control system. These models identify key molecular interactions responsible for the observed physiological properties, and they generate experimentally testable predictions to validate the assumptions made in the models. Ph. D. 2014-03-14T20:17:54Z 2014-03-14T20:17:54Z 2008-10-23 2008-11-03 2008-11-25 2008-11-25 Dissertation etd-11032008-114621 http://hdl.handle.net/10919/29443 http://scholar.lib.vt.edu/theses/available/etd-11032008-114621/ tonglidisnov19.pdf In Copyright http://rightsstatements.org/vocab/InC/1.0/ application/pdf Virginia Tech |
collection |
NDLTD |
format |
Others
|
sources |
NDLTD |
topic |
mathematical modeling systems biology apoptosis p53 NFkB |
spellingShingle |
mathematical modeling systems biology apoptosis p53 NFkB Zhang, Tongli Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death |
description |
In a multi-cellular organism, cells constantly receive signals on their internal condition and surrounding environment. In response to various signals, cells proliferate, move around or even undergo suicide. The signal-response is controlled by complex molecular machinery, understanding of which is an important goal of basic molecular biological research. Such understanding is also valuable for clinical application, since lethal diseases like cancer show maladaptive responses to growth-regulating signals. Because the multiple feedbacks in the molecular regulatory machinery obscure cause-effect relations, it is hard to understand these control systems by intuition alone. Here we translate the molecular interactions into differential equations and recapture the cellular physiological properties with the help of numerical simulations and non-linear dynamical tools. The models address the physiological features of programmed cell death, the cell fate decision by p53 and the dynamics of the NF-?B control system. These models identify key molecular interactions responsible for the observed physiological properties, and they generate experimentally testable predictions to validate the assumptions made in the models. === Ph. D. |
author2 |
Genetics, Bioinformatics, and Computational Biology |
author_facet |
Genetics, Bioinformatics, and Computational Biology Zhang, Tongli |
author |
Zhang, Tongli |
author_sort |
Zhang, Tongli |
title |
Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death |
title_short |
Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death |
title_full |
Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death |
title_fullStr |
Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death |
title_full_unstemmed |
Mathematical Models of Some Signaling Pathways Regulating Cell Survival and Death |
title_sort |
mathematical models of some signaling pathways regulating cell survival and death |
publisher |
Virginia Tech |
publishDate |
2014 |
url |
http://hdl.handle.net/10919/29443 http://scholar.lib.vt.edu/theses/available/etd-11032008-114621/ |
work_keys_str_mv |
AT zhangtongli mathematicalmodelsofsomesignalingpathwaysregulatingcellsurvivalanddeath |
_version_ |
1719341576115716096 |