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MODEL1302010009 - Pitkanen2014 - Metabolic reconstruction of Magnaporthe grisea using CoReCo

 

The following model is part of the non-curated branch of BioModels Database. While the syntax of the model has been verified, its semantics remains unchecked. Any annotation present in the models is not a product of BioModels' annotators. We are doing our best to incorporate this model into the curated branch as soon as possible. In the meantime, we display only limited metadata here. For further information about the model, please download the SBML file.


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Reference Publication
Publication ID: 24516375
Pitkänen E, Jouhten P, Hou J, Syed MF, Blomberg P, Kludas J, Oja M, Holm L, Penttilä M, Rousu J, Arvas M.
Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species.
PLoS Comput. Biol. 2014 Feb; 10(2): e1003465
Department of Computer Science, University of Helsinki, Helsinki, Finland ; Department of Medical Genetics, Genome-Scale Biology Research Program, University of Helsinki, Helsinki, Finland.  [more]
Model
Original Model: MODEL1302010009.origin
Submitter: Esa Pitkänen
Submission Date: 01 Feb 2013 17:31:25 UTC
Last Modification Date: 02 Mar 2014 17:41:23 UTC
Creation Date: 20 Jan 2013 12:00:00 UTC
Non kinetic model: network icon.
Encoders:  Esa Pitkanen
bqbiol:isVersionOf Gene Ontology cellular metabolic process
bqbiol:hasTaxon Taxonomy Magnaporthe grisea
Notes
Pitkanen2014 - Metabolic reconstruction of Magnaporthe grisea 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:

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/.

To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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