S92A: Dynamic modeling of metabolism. The cybernetic approach

Dynamic modeling of metabolism (Song and Ramkrishna[1] [2]) based on the cybernetic concept (Kompala et al[3]; Young and Ramkrishna[4]) is reviewed demonstrating its predictive capabilities.  The talk will: (i) introduce its basic tenets, (ii) expound its relationship to other approaches to modeling metabolism, and (iii) to reveal its unique dynamic capabilities. The framework is shown to provide eloquent support for goal-oriented explanations of regulatory biological phenomena within the cause-and-effect methodology of science through experimental conformation of exacting predictions.  It is further shown that relatively sparse dynamic data on wild-type strains suffice to predict the dynamic behavior of numerous gene knockout mutant strains providing a promising framework for metabolic engineering with the focus on productivity of targeted products.

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[1] Song, Hyun-Seob and D. Ramkrishna, “Prediction of Metabolic Function from Limited Data: Lumped Hybrid Cybernetic Modeling (L-HCM),” Biotechnol. & Bioeng., 106, 271-284, 2010.

[2] Song, Hyun-Seob and D. Ramkrishna, “Cybernetic Models based on Lumped Elementary Modes Accurately Predict Metabolic Function of Multiple Strains,”, Biotechnol. & Bioeng., 127-140, 2011.

[3] Kompala, D.S., D. Ramkrishna., N.B. Jansen and G.T. Tsao, "Investigation of Bacterial Growth on Mixed Substrates.  Experimental Evaluation of Cybernetic Models," Biotech. & Bioeng., 28, 1044-1056, 1986.

[4] Young, J. D. and D. Ramkrishna, “On the Matching & Proportional Laws of Cybernetic Models,” Biotech.Progress, 23, 83-99, 2007.

See more of: Recent advances in computational approaches for metabolic engineering
See more of: Invited Oral Papers

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