Gene regulatory networks simplified by nonlinear balanced truncation

Anke Meyer-Bäse; Fabian Theis

doi:10.1117/12.777292

16 April 2008 Gene regulatory networks simplified by nonlinear balanced truncation

Anke Meyer-Bäse, Fabian Theis

Author Affiliations +

Proceedings Volume 6979, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI; 69790C (2008) https://doi.org/10.1117/12.777292
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

The complexity of gene regulatory networks described by coupled nonlinear differential equations is often an obstacle for analysis purposes. Therefore, the development of effective model reduction techniques is of paramount importance in the field of systems biology. In this paper, we apply the theory of nonlinear balanced truncation for model reduction for gene regulatory networks based only on standard matrix computations. The method is based on finding a controllability and observability function of the nonlinear system and thus obtain a balanced representation that produces singular value functions which are functions of the state. As a result, we obtain a ranked contribution of the states from an input - output perspective.

Citation Download Citation

Anke Meyer-Bäse and Fabian Theis "Gene regulatory networks simplified by nonlinear balanced truncation", Proc. SPIE 6979, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI, 69790C (16 April 2008); https://doi.org/10.1117/12.777292

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