Logical transformation of genome-scale metabolic models for gene level applications and analysis.
Bioinformatics
; 31(14): 2324-31, 2015 Jul 15.
Article
em En
| MEDLINE
| ID: mdl-25735769
ABSTRACT
MOTIVATION In recent years, genome-scale metabolic models (GEMs) have played important roles in areas like systems biology and bioinformatics. However, because of the complexity of gene-reaction associations, GEMs often have limitations in gene level analysis and related applications. Hence, the existing methods were mainly focused on applications and analysis of reactions and metabolites. RESULTS:
Here, we propose a framework named logic transformation of model (LTM) that is able to simplify the gene-reaction associations and enables integration with other developed methods for gene level applications. We show that the transformed GEMs have increased reaction and metabolite number as well as degree of freedom in flux balance analysis, but the gene-reaction associations and the main features of flux distributions remain constant. In addition, we develop two methods, OptGeneKnock and FastGeneSL by combining LTM with previously developed reaction-based methods. We show that the FastGeneSL outperforms exhaustive search. Finally, we demonstrate the use of the developed methods in two different case studies. We could design fast genetic intervention strategies for targeted overproduction of biochemicals and identify double and triple synthetic lethal gene sets for inhibition of hepatocellular carcinoma tumor growth through the use of OptGeneKnock and FastGeneSL, respectively. AVAILABILITY AND IMPLEMENTATION Source code implemented in MATLAB, RAVEN toolbox and COBRA toolbox, is public available at https//sourceforge.net/projects/logictransformationofmodel.
Texto completo:
1
Coleções:
01-internacional
Temas:
Geral
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Tipos_de_cancer
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Outros_tipos
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
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Proteínas de Escherichia coli
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Proteínas de Saccharomyces cerevisiae
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Biologia de Sistemas
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Redes e Vias Metabólicas
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Neoplasias Hepáticas
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Modelos Biológicos
Limite:
Humans
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2015
Tipo de documento:
Article