Mardinoglu2013 - Genome-scale metabolic model (HMR version 1.0) - human adipocytes (iAdipocytes1809)
Ontology highlight
ABSTRACT:
SUBMITTER: 
Adil Mardinoglu
PROVIDER: MODEL1402200001 | BioModels | 2005-01-01
REPOSITORIES: BioModels
Publications
Integration of clinical data with a genome-scale metabolic model of the human adipocyte.
Mardinoglu Adil A Agren Rasmus R Kampf Caroline C Asplund Anna A Nookaew Intawat I Jacobson Peter P Walley Andrew J AJ Froguel Philippe P Carlsson Lena M LM Uhlen Mathias M Nielsen Jens J
Molecular systems biology 20130101
We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By combining this with previously published adipocyte-specific proteome data, we identified proteins associated with 7340 genes in human adipocytes. This information was used to reconstruct a comprehensive and functional genome-scale metabolic model of adipocyte metabolism. The resulting metabolic model, iAdipocytes1809, enables mechanistic insigh ...[more]
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Abstract:
In this chapter, we describe the steps needed to create a kinetic model of a metabolic pathway based on kinetic data from experimental measurements and literature review. Our methodology is presented by utilizing the example of trehalose metabolism in yeast. The biology of the trehalose cycle is briefly reviewed and discussed.
This SBML model is made available under the Creative Commons Attribution-Share Alike 3.0 Unported Licence (see www.creativecommons.org
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This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2012 The BioModels.net Team.
For more information see the terms of use
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To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
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,
Abstract:
Background
Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism.
Results
Combining in silico tools and expert manual curation, we have produced an accurate genome-scale metabolic model for Y. lipolytica. Using a scaffold derived from a functional metabolic model of the well-studied but phylogenetically distant yeast S. cerevisiae, we mapped conserved reactions, rewrote gene associations, added species-specific reactions and inflected specialized copies of scaffold reactions to account for species-specific expansion of protein families. We used physiological measures obtained under lab conditions to validate our predictions.
Conclusions
Y. lipolytica iNL895represents the first well-annotated metabolic model of an oleaginous yeast, providing a reference for future metabolic improvement, and a starting point for the metabolic reconstruction of other species in the Yarrowia clade and other oleaginous yeasts.
Note:
This SBML representation of the Yarrowia lipolytica metabolic network is made available under the Creative Commons Attribution-Share Alike 3.0 Unported Licence (see www.creativecommons.org).
Nicolas Loira (loira@inria.fr, nloira@gmail.com); based on S.cerevisiae model yeast_4.36.xml (Herrgard, 2008)
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This model is hosted on BioModels Database
and identified by: MODEL1204120000
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To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. PMID: 20587024
.
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>http://creativecommons.org/publicdomain/zero/1.0/] for more information.
2005-01-01 | MODEL1204120000 | BioModels
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Project description:This is the model described in the article:
Towards a genome-scale kinetic model of cellular metabolism
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, doi: 10.1186/1752-0509-4-6
Abstract:
CKGROUND: Advances in bioinformatic techniques and analyses have led to the availability of genome-scale metabolic reconstructions. The size and complexity of such networks often means that their potential behaviour can only be analysed with constraint-based methods. Whilst requiring minimal experimental data, such methods are unable to give insight into cellular substrate concentrations. Instead, the long-term goal of systems biology is to use kinetic modelling to characterize fully the mechanics of each enzymatic reaction, and to combine such knowledge to predict system behaviour.
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CONCLUSIONS: Our modelling framework may be considered a stepping-stone toward the long-term goal of a fully-parameterized model of yeast metabolism. The model (see additional file 1) is available in SBML format from the BioModels database (BioModels ID: MODEL1001200000) and at http://www.mcisb.org/resources/genomescale/
.
This SBML representation of the yeast metabolic network is made available under the Creative Commons Attribution-Share Alike 3.0 Unported Licence (see www.creativecommons.org).
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
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