Identification of complex biological network classes using extended correlation analysis

Lee, Dennis and Yue, Hong and Yu, Jun and Marshall, Stephen; Kariwala, Vinay and Samavedham, Lakshminarayanan and Braatz, Richard D, eds. (2012) Identification of complex biological network classes using extended correlation analysis. In: Advanced control of chemical processes. International Federation of Automatic Control (IFAC), SGP, pp. 457-462. ISBN 9783902823052 (https://doi.org/10.3182/20120710-4-SG-2026.00071)

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Abstract

Modeling and analysis of complex biological networks necessitates suitable handling of data on a parallel scale. Using the IkB-NF-kB 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.

ORCID iDs

Lee, Dennis, Yue, Hong ORCID logoORCID: https://orcid.org/0000-0003-2072-6223, Yu, Jun ORCID logoORCID: https://orcid.org/0000-0002-3673-6760 and Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628; Kariwala, Vinay, Samavedham, Lakshminarayanan and Braatz, Richard D
CORE (COnnecting REpositories)