Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions.

ABSTRACT:

Background

The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruction contains gaps and possible errors. There are a total of 208 blocked metabolites in iJO1366, representing gaps in the network.

Results

A new model improvement workflow was developed to compare model based phenotypic predictions to experimental data to fill gaps and correct errors. A Keio Collection based dataset of E. coli gene essentiality was obtained from literature data and compared to model predictions. The SMILEY algorithm was then used to predict the most likely missing

SUBMITTER: Orth JD 

PROVIDER: S-EPMC3423039 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature