Parameter identification for nonlinear biological phenomena modeled by S-systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 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
Event12th International Multi-Conference on Systems, Signals and Devices, SSD 2015 - Mahdia, Tunisia
Duration: 16 Mar 201519 Mar 2015

Other

Other12th International Multi-Conference on Systems, Signals and Devices, SSD 2015
CountryTunisia
CityMahdia
Period16/3/1519/3/15

Fingerprint

Identification (control systems)
Biological systems
Curing
Nonlinear systems
Time series
Dynamic models

Keywords

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

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Control and Systems Engineering

Cite this

Mansouri, M., Avci, O., Nounou, H., & Nounou, M. (2015). Parameter identification for nonlinear biological phenomena modeled by S-systems. In 12th International Multi-Conference on Systems, Signals and Devices, SSD 2015 [7348187] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSD.2015.7348187

Parameter identification for nonlinear biological phenomena modeled by S-systems. / Mansouri, Majdi; Avci, Onur; Nounou, Hazem; Nounou, Mohamed.

12th International Multi-Conference on Systems, Signals and Devices, SSD 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7348187.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mansouri, M, Avci, O, Nounou, H & Nounou, M 2015, Parameter identification for nonlinear biological phenomena modeled by S-systems. in 12th International Multi-Conference on Systems, Signals and Devices, SSD 2015., 7348187, Institute of Electrical and Electronics Engineers Inc., 12th International Multi-Conference on Systems, Signals and Devices, SSD 2015, Mahdia, Tunisia, 16/3/15. https://doi.org/10.1109/SSD.2015.7348187
Mansouri M, Avci O, Nounou H, Nounou M. Parameter identification for nonlinear biological phenomena modeled by S-systems. In 12th International Multi-Conference on Systems, Signals and Devices, SSD 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7348187 https://doi.org/10.1109/SSD.2015.7348187
Mansouri, Majdi ; Avci, Onur ; Nounou, Hazem ; Nounou, Mohamed. / Parameter identification for nonlinear biological phenomena modeled by S-systems. 12th International Multi-Conference on Systems, Signals and Devices, SSD 2015. Institute of Electrical and Electronics Engineers Inc., 2015.
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