Systems biology is an interdisciplinary field that combines engineering and molecular biology to better understand the 'design principles' of biological systems. One of the main goals in systems biology is to understand and map complex biological networks. In order to achieve this goal, tools able to process the non-linearity and high dimensionality of biological systems are urgently needed. To develop, test and benchmark tools for investigation of biological processes, it is important to utilize a model system that is able to provide a glimpse of complexity found in higher organisms, and be simple enough such that detailed studies can be performed rapidly, accurately, and reproducibly. Here, we have developed a system-identification framework for the extraction of quantitative and mechanistic information about causal relationship among genes using the canonical galactose utilization pathway in Saccharomyces cerevisiae. This framework, referred to as s&barbelow;ystematic g&barbelow;ene p&barbelow;erturbation a&barbelow;nalysis (SGPA), is based on the effects of systematic pair-wise gene deletions. In essence, the method establishes dynamical models of the regulatory network from single-cell measurements of steady-state input-output relationships, in systematically perturbed networks. SGPA framework is successful in identifying the network structure for the GAL system. This strategy leads the way to a better application of available resources and provides a scalable framework for system-identification and reverse-engineering of biological networks based on in vivo systematic data generation.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/28254 |
| Date | January 2009 |
| Creators | Abedi, Vida |
| Publisher | University of Ottawa (Canada) |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 206 p. |
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