Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA324641 | ENA |
REPOSITORIES: ENA
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Project description:Selvarasu2009 - Genome-scale metabolic
network of Mus Musculus (iSS724)
This model is described in the article:
Genome-scale modeling and in
silico analysis of mouse cell metabolic network.
Selvarasu S, Karimi IA, Ghim GH, Lee
DY.
Mol Biosyst 2010 Jan; 6(1):
152-161
Abstract:
Genome-scale metabolic modeling has been successfully
applied to a multitude of microbial systems, thus improving our
understanding of their cellular metabolisms. Nevertheless, only
a handful of works have been done for describing mammalian
cells, particularly mouse, which is one of the important model
organisms, providing various opportunities for both biomedical
research and biotechnological applications. Presented herein is
a genome-scale mouse metabolic model that was systematically
reconstructed by improving and expanding the previous generic
model based on integrated biochemical and genomic data of Mus
musculus. The key features of the updated model include
additional information on gene-protein-reaction association,
and improved network connectivity through lipid, amino acid,
carbohydrate and nucleotide biosynthetic pathways. After
examining the model predictability both quantitatively and
qualitatively using constraints-based flux analysis, the
structural and functional characteristics of the mouse
metabolism were investigated by evaluating network
statistics/centrality, gene/metabolite essentiality and their
correlation. The results revealed that overall mouse metabolic
network is topologically dominated by highly connected and
bridging metabolites, and functionally by lipid metabolism that
most of essential genes and metabolites are from. The current
in silico mouse model can be exploited for understanding and
characterizing the cellular physiology, identifying potential
cell engineering targets for the enhanced production of
recombinant proteins and developing diseased state models for
drug targeting.
This model is hosted on
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and identified by:
MODEL1507180042.
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To the extent possible under law, all copyright and related or
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2015-07-30 | MODEL1507180042 | BioModels
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