Sporobolomyces roseus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA763771 | ENA |
REPOSITORIES: ENA
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Project description:Pitkanen2014 - Metabolic reconstruction of Sporobolomyces roseus using CoReCo
This model was reconstructed with the CoReCo method (Comparative ReConstruction of genome-scale metabolic networks) from protein sequence and phylogeny data.
This model is described in the article:
Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species
Esa Pitkänen, Paula Jouhten, Jian Hou, Muhammad Fahad Syed, Peter Blomberg, Jana Kludas, Merja Oja, Liisa Holm, Merja Penttilä, Juho Rousu, Mikko Arvas
PLoS Comput Biol. 2014 Feb 6;10(2):e1003465
Abstract:
We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.
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2014-03-02 | MODEL1302010036 | BioModels
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