Extrapolation of metabolic pathways as an aid to modelling completely sequenced nonSaccharomyces yeasts.

Florian Iragne 1, 2 Macha Nikolski 1, 2 David James Sherman 1, 2
2 MAGNOME - Models and Algorithms for the Genome
INRIA Futurs, Université Sciences et Technologies - Bordeaux 1, École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), CNRS - Centre National de la Recherche Scientifique : UMR5800
Abstract : Mathematical models of biological processes for the model yeast Saccharomyces cerevisiae are the subject of intensive effort and are available in increasing numbers. An open question is whether such models are informative for related yeasts of biotechnological and medical interest that will not themselves benefit from an equivalent effort. In this study, we assess a method for extrapolating reference models to other completely sequenced yeasts, using a combination of graph-theoretic analysis and reliable identification of homologous genes using Génolevures protein families. In this first assessment, we focus on subtractive modeling, identified through the correlated loss of input and output ports in metabolic pathways. We confirm that the major, highly connected, pathways of central metabolism are conserved and might be universal. In 60-80% of our results, further analysis is not required to determine whether the pathway is lost or conserved, so that our method can be systematically applied as a first step in developing species-specific models.
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FEMS Yeast Research, Oxford University Press (OUP), 2008, 8 (1), pp.132-9. 〈10.1111/j.1567-1364.2007.00290.x〉
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https://hal.inria.fr/inria-00202723
Contributeur : David James Sherman <>
Soumis le : mardi 8 janvier 2008 - 03:35:49
Dernière modification le : jeudi 11 janvier 2018 - 06:21:04

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Florian Iragne, Macha Nikolski, David James Sherman. Extrapolation of metabolic pathways as an aid to modelling completely sequenced nonSaccharomyces yeasts.. FEMS Yeast Research, Oxford University Press (OUP), 2008, 8 (1), pp.132-9. 〈10.1111/j.1567-1364.2007.00290.x〉. 〈inria-00202723〉

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