Title :
Set Membership (In) Validation of nonlinear positive models for biological systems
Author :
Falugi, P. ; Giarré, L.
Author_Institution :
DSI, Universita di Firenze
Abstract :
The complexity of biology needs quantitative tools in order to support and validate biologists intuition and traditional qualitative descriptions. In this paper, nonlinear positive models with constraints for biological systems are validated/invalidated in a worst-case deterministic setting. These models are useful for the analysis of the DNA and RNA evolution and for the description of the population dynamics of viruses and bacteria. The conditional central estimate and the uncertainty intervals are determined in order to validate/invalidate the model. The effectiveness of the proposed procedure has been illustrated by means of simulation experiments
Keywords :
biology; nonlinear systems; DNA evolution; RNA evolution; bacteria; biological systems; nonlinear positive model; population dynamics; set membership; uncertainty intervals; viruses; Biological system modeling; Biological systems; Chemicals; DNA; Equations; Evolution (biology); Genetic mutations; RNA; Sequences; Viruses (medical);
Conference_Titel :
Decision and Control, 2006 45th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
1-4244-0171-2
DOI :
10.1109/CDC.2006.377371
