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Dissertation
New methods in computational systems biology
Doctor of Philosophy (Ph.D.), Drexel University
Mar 2008
DOI:
https://doi.org/10.17918/etd-2810
Abstract
Systems biology strives to reach greater understanding of biological function through an integrative, multidisciplinary approach utilizing experimentation, theory, and simulation in equal measures. Drawing from the traditionally distinct fields of biology, chemistry, physics, engineering, mathematics, computer science, informatics, and medicine, systems biology regards biological components as acting in tandem in a unified hierarchical system over a wide range of scales, from nano-scale (proteins and small molecules) to micro-scale (organelles and cells) to macro-scale (tissue and organs). Within this burgeoning field, computational modeling of cell signaling serves not only to validate theoretical and experimental findings, but also to provide quantitative and even predictive analysis of biochemical networks and intracellular machinery. In this thesis, a model of the canonical MAPK signal transduction pathway (well studied for its role in a large percentage of cancers) is analyzed using the custom simulation software package CellSim as a tool for predicting targets for effective anti-cancer drugs, as well as predicting the effects of such drugs on non-cancerous cells. Furthermore, computational tools and methods are developed for extending such purely kinetic models of intracellular signaling into the spatio-temporal realm, introducing locality, transport, and cell geometry.
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Details
- Title
- New methods in computational systems biology
- Creators
- David J. Miller - DU
- Contributors
- Avijit Ghosh (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- College of Arts and Sciences; Physics; Drexel University
- Other Identifier
- 2810; 991014632258904721