A system biology approach for the steady-state analysis of gene signaling networks

Authors:
Purvesh Khatri;Sorin Draghici;Adi L. Tarca;Sonia S. Hassan;Roberto Romero
Affiliations:
Department of Computer Science, Wayne State University;Department of Computer Science, Wayne State University;Department of Computer Science, Wayne State University and Perinatology Research Branch, NIH, NICHD, Detroit, MI;Perinatology Research Branch, NIH, NICHD, Detroit, MI;Perinatology Research Branch, NIH, NICHD, Detroit, MI
Venue:
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Year:
2007

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Abstract

The existing approaches used to identify the relevant pathways in a given condition do not consider a number of important biological factors such as magnitude of each gene's expression change, their position and interactions in the given pathways, etc. Recently, an impact analysis approach was proposed that considers these crucial biological factors to analyze regulatory pathways at systems biology level. This approach calculates perturbations induced by each gene in a pathway, and propagates them through the entire pathway to compute an impact factor for the given pathway. Here we propose an alternative approach that uses a linear system to compute the impact factor. Our proposed approach eliminates the possible stability problems when the perturbations are propagated through a pathway that contains positive feedback loops. Additionally, the proposed approach is able to consider the type of genes when calculating the impact factors.