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Identification of a model of non-esterified fatty acids dynamics through genetic algorithms: The case of women with a history of gestational diabetes

Articolo
Data di Pubblicazione:
2011
Abstract:
Elevation in non-esterified fatty acids (NEFA) has been shown to modulate insulin secretion and it is considered as a risk factor for the development of type 2 diabetes. Here we present a method that complements a mathematical model of NEFA kinetics with genetic algorithms for model identification. The complemented strategy allowed to assess parameters of NEFA kinetics and to get insight into their relationship with insulin during oral glucose tolerance tests in women with former gestational diabetes: (i) providing a reliable estimation of the model parameters, (ii) assuring the usability of the model, and (iii) promoting and facilitating its application in a clinical context. (C) 2011 Elsevier Ltd. All rights reserved.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Gestational diabetes; Mathematical modeling; Model identification; Non-esterified fatty acids; Oral glucose tolerance test; Genetic algorithms
Elenco autori:
Tura, Andrea; Pacini, Giovanni
Autori di Ateneo:
TURA ANDREA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/48270
Pubblicato in:
COMPUTERS IN BIOLOGY AND MEDICINE
Journal
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URL

http://www.ncbi.nlm.nih.gov/pubmed/21333978
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