Parameter estimation and sensitivity analysis of biological systems with memory

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

Abstract

Parameter estimation for biological systems is an important topic and considered as an inverse problem. In this paper, we provide a general computational technique for parameter estimations of biological systems described by delay differential equations, using least squares approach. Sensitivity analysis is an important tool for understanding a particular model, which is considered as an issue of stability with respect to structural perturbations in the model. We introduce a variational method to evaluate sensitivity of the state variables to small perturbations in the initial conditions and parameters appear in the model. The consistency of neutral delay differential equations with bacterial cell growth is shown, as a numerical example, by fitting the model to real observations.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Bioinformatics and Computational Biology, BICOB 2016
EditorsNurit Haspel, Thomas Ioerger
PublisherThe International Society for Computers and Their Applications (ISCA)
Pages97-102
Number of pages6
ISBN (Electronic)9781943436033
Publication statusPublished - 2016
Event8th International Conference on Bioinformatics and Computational Biology, BICOB 2016 - Las Vegas, United States
Duration: Apr 4 2016Apr 6 2016

Publication series

NameProceedings of the 8th International Conference on Bioinformatics and Computational Biology, BICOB 2016

Other

Other8th International Conference on Bioinformatics and Computational Biology, BICOB 2016
Country/TerritoryUnited States
CityLas Vegas
Period4/4/164/6/16

Keywords

  • Biological systems
  • DDEs
  • Parameter estimation
  • Sensitivity analysis
  • Time-lags

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Information Systems
  • Biomedical Engineering
  • Electrical and Electronic Engineering
  • Health Informatics

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