Simple topological properties predict functional misannotations in a metabolic network.

ABSTRACT:

Motivation

Misannotation in sequence databases is an important obstacle for automated tools for gene function annotation, which rely extensively on comparison with sequences with known function. To improve current annotations and prevent future propagation of errors, sequence-independent tools are, therefore, needed to assist in the identification of misannotated gene products. In the case of enzymatic functions, each functional assignment implies the existence of a reaction within the organism's metabolic network; a first approximation to a genome-scale metabolic model can be obtained directly from an automated genome annotation. Any obvious problems in the network, such as dead end or disconnected reactions, can, therefore, be strong indications of misannotation.

Results

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SUBMITTER: Liberal R 

PROVIDER: S-EPMC3694667 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature