Literature DB >> 12604132

Structural identifiability for a class of non-linear compartmental systems using linear/non-linear splitting and symbolic computation.

Michael J Chapman1, Keith R Godfrey, Michael J Chappell, Neil D Evans.   

Abstract

Under certain controllability and observability restrictions, two different parameterisations for a non-linear compartmental model can only have the same input-output behaviour if they differ by a locally diffeomorphic change of basis for the state space. With further restrictions, it is possible to gain valuable information with respect to identifiability via a linear analysis. Examples are presented where non-linear identifiability analyses are substantially simplified by means of an initial linear analysis. For complex models, with four or more compartments, this linear analysis can prove lengthy to perform by hand and so symbolic computation has been employed to aid this procedure.

Mesh:

Year:  2003        PMID: 12604132     DOI: 10.1016/s0025-5564(02)00223-7

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  6 in total

1.  Structural identifiability analysis of pharmacokinetic models using DAISY: semi-mechanistic gastric emptying models for 13C-octanoic acid.

Authors:  Kayode Ogungbenro; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-02-24       Impact factor: 2.745

2.  A Priori Identifiability Analysis of Cardiovascular Models.

Authors:  Jonathan A Kirk; Maria P Saccomani; Sanjeev G Shroff
Journal:  Cardiovasc Eng Technol       Date:  2013-12       Impact factor: 2.495

3.  An iterative identification procedure for dynamic modeling of biochemical networks.

Authors:  Eva Balsa-Canto; Antonio A Alonso; Julio R Banga
Journal:  BMC Syst Biol       Date:  2010-02-17

4.  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

Review 5.  Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

Authors:  J Geoffrey Chase; Jean-Charles Preiser; Jennifer L Dickson; Antoine Pironet; Yeong Shiong Chiew; Christopher G Pretty; Geoffrey M Shaw; Balazs Benyo; Knut Moeller; Soroush Safaei; Merryn Tawhai; Peter Hunter; Thomas Desaive
Journal:  Biomed Eng Online       Date:  2018-02-20       Impact factor: 2.819

6.  Best Practices to Maximize the Use and Reuse of Quantitative and Systems Pharmacology Models: Recommendations From the United Kingdom Quantitative and Systems Pharmacology Network.

Authors:  Lourdes Cucurull-Sanchez; Michael J Chappell; Vijayalakshmi Chelliah; S Y Amy Cheung; Gianne Derks; Mark Penney; Alex Phipps; Rahuman S Malik-Sheriff; Jon Timmis; Marcus J Tindall; Piet H van der Graaf; Paolo Vicini; James W T Yates
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-03-22
  6 in total

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