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Integration of transcription and flux data reveals molecular paths associated with differences in oxygen-dependent phenotypes of Saccharomyces cerevisiae
VTT Technical Research Centre of Finland, Espoo, Finland; LifeGlimmer GmbH, Berlin, Germany; Chemistry Building, Wageningen, Netherlands.
VTT Technical Research Centre of Finland, Espoo, Finland.
VTT Technical Research Centre of Finland, Espoo, Finland.
VTT Technical Research Centre of Finland, Espoo, Finland.
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2014 (English)In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 8, article id 16Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Saccharomyces cerevisiae is able to adapt to a wide range of external oxygen conditions. Previously, oxygen-dependent phenotypes have been studied individually at the transcriptional, metabolite, and flux level. However, the regulation of cell phenotype occurs across the different levels of cell function. Integrative analysis of data from multiple levels of cell function in the context of a network of several known biochemical interaction types could enable identification of active regulatory paths not limited to a single level of cell function.

RESULTS: The graph theoretical method called Enriched Molecular Path detection (EMPath) was extended to enable integrative utilization of transcription and flux data. The utility of the method was demonstrated by detecting paths associated with phenotype differences of S. cerevisiae under three different conditions of oxygen provision: 20.9%, 2.8% and 0.5%. The detection of molecular paths was performed in an integrated genome-scale metabolic and protein-protein interaction network.

CONCLUSIONS: The molecular paths associated with the phenotype differences of S. cerevisiae under conditions of different oxygen provisions revealed paths of molecular interactions that could potentially mediate information transfer between processes that respond to the particular oxygen availabilities.

Place, publisher, year, edition, pages
BioMed Central, 2014. Vol. 8, article id 16
National Category
Cell Biology Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-63692DOI: 10.1186/1752-0509-8-16ISI: 000334796500001PubMedID: 24528924Scopus ID: 2-s2.0-84894366271OAI: oai:DiVA.org:oru-63692DiVA, id: diva2:1169257
Note

Funding agencies:

Academy of Finland through the Centre of Excellence in White Biotechnology-Green Chemistry 118573 

Academy of Finland 140380 

Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2018-01-23Bibliographically approved

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Oresic, Matej

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