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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biotechnology and Bi...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biotechnology and Bioengineering
Article . 2004 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Metabolic pathway analysis of yeast strengthens the bridge between transcriptomics and metabolic networks

Authors: Tunahan, Cakir; Betül, Kirdar; Kutlu O, Ulgen;

Metabolic pathway analysis of yeast strengthens the bridge between transcriptomics and metabolic networks

Abstract

AbstractCentral carbon metabolism of the yeast Saccharomyces cerevisiae was analyzed using metabolic pathway analysis tools. Elementary flux modes for three substrates (glucose, galactose, and ethanol) were determined using the catabolic reactions occurring in yeast. Resultant elementary modes were used for gene deletion phenotype analysis and for the analysis of robustness of the central metabolism and network functionality. Control‐effective fluxes, determined by calculating the efficiency of each mode, were used for the prediction of transcript ratios of metabolic genes in different growth media (glucose–ethanol and galactose–ethanol). A high correlation was obtained between the theoretical and experimental expression levels of 38 genes when ethanol and glucose media were considered. Such analysis was shown to be a bridge between transcriptomics and fluxomics. Control‐effective flux distribution was found to be promising in in silico predictions by incorporating functionality and regulation into the metabolic network structure. © 2004 Wiley Periodicals, Inc.

Related Organizations
Keywords

Ethanol, Transcription, Genetic, Genes, Fungal, Galactose, Saccharomyces cerevisiae, Models, Biological, Carbon, Culture Media, Glucose, Gene Expression Regulation, Fungal, Biomass, Gene Deletion

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    influence
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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
67
Average
Top 10%
Top 10%
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