Integration of gene expression data into genome-scale metabolic models
| Autor: | Mats Åkesson, Jochen Förster, Jens Nielsen |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Transcription
Genetic Systems biology Saccharomyces cerevisiae Bioengineering Chemostat Computational biology Applied Microbiology and Biotechnology Transcriptome Gene Expression Regulation Fungal Databases Genetic Oligonucleotide Array Sequence Analysis Regulation of gene expression biology Models Genetic business.industry Quantitative Biology::Molecular Networks Gene Expression Profiling Fungal genetics biology.organism_classification Quantitative Biology::Genomics Biotechnology Gene expression profiling Metabolic network modelling Genome Fungal business |
| Zdroj: | Metabolic engineering. 6(4) |
| ISSN: | 1096-7176 |
| Popis: | A framework for integration of transcriptome data into stoichiometric metabolic models to obtain improved flux predictions is presented. The key idea is to exploit the regulatory information in the expression data to give additional constraints on the metabolic fluxes in the model. Measurements of gene expression from chemostat and batch cultures of Saccharomyces cerevisiae were combined with a recently developed genome-scale model, and the computed metabolic flux distributions were compared to experimental values from carbon labeling experiments and metabolic network analysis. The integration of expression data resulted in improved predictions of metabolic behavior in batch cultures, enabling quantitative predictions of exchange fluxes as well as qualitative estimations of changes in intracellular fluxes. A critical discussion of correlation between gene expression and metabolic fluxes is given. |
| Databáze: | OpenAIRE |
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