Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System CharacterizationsStructural Analysis of Biological Networks

A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System... [We introduce the idea of structural analysis of biological network models. In general, mathematical representations of molecular systems are affected by parametric uncertainty: experimental validation of models is always affected by errors and intrinsic variability of biological samples. Using uncertain models for predictions is a delicate task. However, given a plausible representation of a system, it is often possible to reach general analytical conclusions on the system’s admissible dynamic behaviors, regardless of specific parameter values: in other words, we say that certain behaviors are structural for a given model. Here we describe a parameter-free, qualitative modeling framework and we focus on several case studies, showing how many paradigmatic behaviors such as multistationarity or oscillations can have a structural nature. We highlight that classical control theory methods are extremely helpful in investigating structural properties.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System CharacterizationsStructural Analysis of Biological Networks

Loading next page...
 
/lp/springer-journals/a-systems-theoretic-approach-to-systems-and-synthetic-biology-i-models-cBwv0gdqYX

References (42)

Publisher
Springer Netherlands
Copyright
© Springer Science+Business Media Dordrecht 2014
ISBN
978-94-017-9040-6
Pages
47 –71
DOI
10.1007/978-94-017-9041-3_2
Publisher site
See Chapter on Publisher Site

Abstract

[We introduce the idea of structural analysis of biological network models. In general, mathematical representations of molecular systems are affected by parametric uncertainty: experimental validation of models is always affected by errors and intrinsic variability of biological samples. Using uncertain models for predictions is a delicate task. However, given a plausible representation of a system, it is often possible to reach general analytical conclusions on the system’s admissible dynamic behaviors, regardless of specific parameter values: in other words, we say that certain behaviors are structural for a given model. Here we describe a parameter-free, qualitative modeling framework and we focus on several case studies, showing how many paradigmatic behaviors such as multistationarity or oscillations can have a structural nature. We highlight that classical control theory methods are extremely helpful in investigating structural properties.]

Published: Jul 4, 2014

Keywords: Biological network; Control theory; Structural analysis; Structural property; Enzymatic networks; Jacobian; Eigenvalue; Chemical reaction network; Robustness; Set invariance; Mitogen activated protein kinase (MAPK)

There are no references for this article.