Parameter identification for nonlinear biological phenomena modeled by S-systems

Majdi Mansouri, Onur Avci, Hazem Nounou, Mohamed Nounou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

For computational modeling of biological systems, one of the major challenges is the identification of the model parameters. It is very beneficial to use easily obtained measurements and estimate variables and/or parameters in such systems. For instance, time-series dynamic genomic data can be used to develop models representing dynamic genetic regulatory networks. These models can be used to design intervention strategies such as understanding the biological system behavior and curing major illnesses. The study shown in this paper focuses on the parameter identification of biological phenomena modeled by S-systems using Particle Filter (PF). While the nonlinear observed system is assumed to progress according to a probabilistic state space model, the results show that the PF has good convergence properties. It is concluded that the good convergence is due to PF's ability to deal with highly nonlinear process models.

Original languageEnglish
Title of host publication12th International Multi-Conference on Systems, Signals and Devices, SSD 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479917587
DOIs
Publication statusPublished - 4 Dec 2015
Externally publishedYes
Event12th International Multi-Conference on Systems, Signals and Devices, SSD 2015 - Mahdia, Tunisia
Duration: 16 Mar 201519 Mar 2015

Publication series

Name12th International Multi-Conference on Systems, Signals and Devices, SSD 2015

Conference

Conference12th International Multi-Conference on Systems, Signals and Devices, SSD 2015
Country/TerritoryTunisia
CityMahdia
Period16/03/1519/03/15

Keywords

  • Cad System in E. coli
  • Parameter identification
  • nonlinear biological systems
  • particle filtering

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