Literature DB >> 20185123

Examples of testing global identifiability of biological and biomedical models with the DAISY software.

Maria Pia Saccomani1, Stefania Audoly, Giuseppina Bellu, Leontina D'Angiò.   

Abstract

DAISY (Differential Algebra for Identifiability of SYstems) is a recently developed computer algebra software tool which can be used to automatically check global identifiability of (linear and) nonlinear dynamic models described by differential equations involving polynomial or rational functions. Global identifiability is a fundamental prerequisite for model identification which is important not only for biological or medical systems but also for many physical and engineering systems derived from first principles. Lack of identifiability implies that the parameter estimation techniques may not fail but any obtained numerical estimates will be meaningless. The software does not require understanding of the underlying mathematical principles and can be used by researchers in applied fields with a minimum of mathematical background. We illustrate the DAISY software by checking the a priori global identifiability of two benchmark nonlinear models taken from the literature. The analysis of these two examples includes comparison with other methods and demonstrates how identifiability analysis is simplified by this tool. Thus we illustrate the identifiability analysis of other two examples, by including discussion of some specific aspects related to the role of observability and knowledge of initial conditions in testing identifiability and to the computational complexity of the software. The main focus of this paper is not on the description of the mathematical background of the algorithm, which has been presented elsewhere, but on illustrating its use and on some of its more interesting features. DAISY is available on the web site http://www.dei.unipd.it/ approximately pia/. 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20185123      PMCID: PMC2933518          DOI: 10.1016/j.compbiomed.2010.02.004

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  8 in total

1.  Global identifiability of nonlinear models of biological systems.

Authors:  S Audoly; G Bellu; L D'Angiò; M P Saccomani; C Cobelli
Journal:  IEEE Trans Biomed Eng       Date:  2001-01       Impact factor: 4.538

2.  Structural identifiability of the parameters of a nonlinear batch reactor model.

Authors:  M J Chappell; K R Godfrey
Journal:  Math Biosci       Date:  1992-03       Impact factor: 2.144

3.  DAISY: a new software tool to test global identifiability of biological and physiological systems.

Authors:  Giuseppina Bellu; Maria Pia Saccomani; Stefania Audoly; Leontina D'Angiò
Journal:  Comput Methods Programs Biomed       Date:  2007-08-20       Impact factor: 5.428

4.  Global identifiability of the parameters of nonlinear systems with specified inputs: a comparison of methods.

Authors:  M J Chappell; K R Godfrey; S Vajda
Journal:  Math Biosci       Date:  1990-11       Impact factor: 2.144

5.  Unappreciation of a priori identifiability in software packages causes ambiguities in numerical estimates.

Authors:  C Cobelli; M P Saccomani
Journal:  Am J Physiol       Date:  1990-06

6.  Effect of dose, molecular size, affinity, and protein binding on tumor uptake of antibody or ligand: a biomathematical model.

Authors:  G D Thomas; M J Chappell; P W Dykes; D B Ramsden; K R Godfrey; J R Ellis; A R Bradwell
Journal:  Cancer Res       Date:  1989-06-15       Impact factor: 12.701

7.  A minimal input-output configuration for a priori identifiability of a compartmental model of leucine metabolism.

Authors:  M P Saccomani; C Cobelli
Journal:  IEEE Trans Biomed Eng       Date:  1993-08       Impact factor: 4.538

8.  Effect of prosthetic sugar groups on the pharmacokinetics of glucose-oxidase.

Authors:  S Demignot; D Domurado
Journal:  Drug Des Deliv       Date:  1987-05
  8 in total
  16 in total

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Journal:  Neuroimage       Date:  2011-04-06       Impact factor: 6.556

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Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

7.  Simultaneous pharmacokinetic model for rolofylline and both M1-trans and M1-cis metabolites.

Authors:  Mark Stroh; Matthew M Hutmacher; Jianmei Pang; Ryan Lutz; Hiroshi Magara; Julie Stone
Journal:  AAPS J       Date:  2013-01-25       Impact factor: 4.009

8.  HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics.

Authors:  Rutao Luo; Michael J Piovoso; Javier Martinez-Picado; Ryan Zurakowski
Journal:  PLoS One       Date:  2012-07-16       Impact factor: 3.240

9.  Structural identifiability of systems biology models: a critical comparison of methods.

Authors:  Oana-Teodora Chis; Julio R Banga; Eva Balsa-Canto
Journal:  PLoS One       Date:  2011-11-22       Impact factor: 3.240

10.  Inference of complex biological networks: distinguishability issues and optimization-based solutions.

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Journal:  BMC Syst Biol       Date:  2011-10-28
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