Literature DB >> 8258446

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

M P Saccomani1, C Cobelli.   

Abstract

To develop a model describing the structure and function of a metabolic system using data from an input-output experiment, it is useful to design a pilot tracer study first which contains a predicted maximal amount of information. Having postulated a physiologically reasonable model structure from the pilot data, two questions arise. First, are the model parameters a priori uniquely identifiable? That is, assuming an error-free model structure and data, can the parameters be uniquely identified from the information content of the pilot experiment? Second, if the model parameters are uniquely identifiable, is the pilot experiment a minimal one? That is, is the pilot experiment necessary and sufficient, in the sense of information content, among feasible experiments to guarantee a priori unique identifiability? The purpose of this paper is to determine a minimal input-output configuration for the a priori unique identifiability of a compartmental model describing the metabolism of leucine, an essential amino acid. The original pilot tracer experiment was a two-stage experiment consisting first of a two input-five output experiment followed by a single input-single output experiment. Here we show to guarantee a priori unique identifiability of the leucine model that the single input-single output experiment is not necessary, and that two of the outputs of the multi-input-multi-output experiment are not required.

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Year:  1993        PMID: 8258446     DOI: 10.1109/10.238464

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  5 in total

1.  Structural identifiability of physiologically based pharmacokinetic models.

Authors:  James W T Yates
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-03-28       Impact factor: 2.745

2.  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

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

Authors:  Maria Pia Saccomani; Stefania Audoly; Giuseppina Bellu; Leontina D'Angiò
Journal:  Comput Biol Med       Date:  2010-02-24       Impact factor: 4.589

4.  The design and analysis of parallel experiments to produce structurally identifiable models.

Authors:  S Y Amy Cheung; James W T Yates; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-01-09       Impact factor: 2.745

5.  Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation.

Authors:  Huan Yang; Hil G E Meijer; Jan R Buitenweg; Stephan A van Gils
Journal:  Front Psychol       Date:  2016-12-05
  5 in total

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