|M.Sc Student||Skolozub Alexandra|
|Subject||Conditional Integration of Biological Pathways|
|Department||Department of Computer Science||Supervisor||Professor Ron Pinter|
|Full Thesis text|
Many biological pathways that describe complex cellular processes are available in public and commercial databases as well as in the literature. However, each item focuses on a particular cellular function. Moreover, pathways differ in the way they are described in different sources, emphasizing complementary aspects of the biological system under study. Considering related pathways in a unified framework is essential for understanding their behavior and for elucidating and refining open issues involving such systems.
We developed a conditional pathway algebra, in which pathways are enriched with both new node types as well as additional edge types providing significantly more expressive power for the description of existing biological phenomena. During conditional pathway integration, some interactions are made dependent upon a specific predicate (the presence/absence of protein, co-regulation, extracellular factors, etc.). Moreover, such integration enables distinguishing between different data sources and points out problematic interactions in the given pathways. We provide a formal definition of the algebra and prove some of its properties (e.g. conditional merge and union), such as closure, commutativity, and the lack of associativity. Some of these operations are essential when applied to several pathways to form an entire (sub)system.
The algebra was implemented in the Pathway Integration Environment (PIE) as a plugin for Cytoscape (www.cytoscape.org). To demonstrate the utility and effectiveness of our method, we have applied it to three well characterized yeast signaling pathways: the (i) Pheromone signaling, (ii) Filamentous growth, and (iii) High osmolarity glycerol pathways. Most of our computational observations are confirmed in the literature.