Identification of Complex Biological Network Classes using Extended Correlation Analysis

Abstract

Modeling and analysis of complex biological networks necessitates suitable handling of data on a parallel scale. Using the IκB-NF-κB pathway model and a basis of sensitivity analysis, analytic methods are presented, extending correlation from the network kinetic reaction rates to that of the rate reactions. Alignment of correlated processed components, vastly outperforming correlation of the data source, advanced sets of biological classes possessing similar network activities. Additional construction generated a naturally structured, cardinally based system for component-specific investigation. The computationally driven procedures are described, with results demonstrating viability as mechanisms useful for fundamental oscillatory network activity investigation.