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Published in: Natural Computing 3/2015

01-09-2015

Combining flux balance analysis and model checking for metabolic network validation and analysis

Authors: Roberto Pagliarini, Mara Sangiovanni, Adriano Peron, Diego di Bernardo

Published in: Natural Computing | Issue 3/2015

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Abstract

Several human diseases are caused by metabolism defects. Discovering the mechanisms that govern the onset and progression of human metabolism-related diseases is not a straightforward process. Computational approaches, such as the flux balance analysis, have been successfully used to extract useful knowledge on the metabolic dysregulation processes from genome-scale network models. In this work, we propose a novel approach which integrates constraint-based techniques with model checking methods, with the aim to extract relevant qualitative information from a metabolic network model. As a case study, we applied our methodology to the simulation and analysis of the primary hyperoxaluria type I, an inherited disease in which the lack of a particular liver enzyme causes the kidney to accumulate excessive amounts of oxalate.

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Metadata
Title
Combining flux balance analysis and model checking for metabolic network validation and analysis
Authors
Roberto Pagliarini
Mara Sangiovanni
Adriano Peron
Diego di Bernardo
Publication date
01-09-2015
Publisher
Springer Netherlands
Published in
Natural Computing / Issue 3/2015
Print ISSN: 1567-7818
Electronic ISSN: 1572-9796
DOI
https://doi.org/10.1007/s11047-014-9419-8

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