Robustness of mathematical models for biological systems

Tian, T. (2004). Robustness of mathematical models for biological systems. In: J. Crawford, 11th Biennial Computational Techniques and Applications Conference: CTAC-2003. 11th Biennial Computational Techniques and Applications Conference: CTAC-2003, Sydney, (565-577). July 2003. doi:10.0000/anziamj.v45i0.908

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Author Tian, T.
Title of paper Robustness of mathematical models for biological systems
Conference name 11th Biennial Computational Techniques and Applications Conference: CTAC-2003
Conference location Sydney
Conference dates July 2003
Proceedings title 11th Biennial Computational Techniques and Applications Conference: CTAC-2003   Check publisher's open access policy
Place of Publication University of Adelaide
Publisher Australian Mathematical Society
Publication Year 2004
Sub-type Fully published paper
DOI 10.0000/anziamj.v45i0.908
Open Access Status DOI
ISSN 1446-8735
Editor J. Crawford
Volume 45
Start page 565
End page 577
Total pages 13
Collection year 2004
Abstract/Summary The robustness of mathematical models for biological systems is studied by sensitivity analysis and stochastic simulations. Using a neural network model with three genes as the test problem, we study robustness properties of synthesis and degradation processes. For single parameter robustness, sensitivity analysis techniques are applied for studying parameter variations and stochastic simulations are used for investigating the impact of external noise. Results of sensitivity analysis are consistent with those obtained by stochastic simulations. Stochastic models with external noise can be used for studying the robustness not only to external noise but also to parameter variations. For external noise we also use stochastic models to study the robustness of the function of each gene and that of the system.
Subjects E1
230116 Numerical Analysis
239901 Biological Mathematics
780101 Mathematical sciences
Q-Index Code E1

 
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Created: Fri, 24 Aug 2007, 05:48:30 EST