Systems approach to refining genome annotation.
Proc Natl Acad Sci U S A
; 103(46): 17480-4, 2006 Nov 14.
Article
em En
| MEDLINE
| ID: mdl-17088549
ABSTRACT
Genome-scale models of Escherichia coli K-12 MG1655 metabolism have been able to predict growth phenotypes in most, but not all, defined growth environments. Here we introduce the use of an optimization-based algorithm that predicts the missing reactions that are required to reconcile computation and experiment when they disagree. The computer-generated hypotheses for missing reactions were verified experimentally in five cases, leading to the functional assignment of eight ORFs (yjjLMN, yeaTU, dctA, idnT, and putP) with two new enzymatic activities and four transport functions. This study thus demonstrates the use of systems analysis to discover metabolic and transport functions and their genetic basis by a combination of experimental and computational approaches.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
3_ND
Base de dados:
MEDLINE
Assunto principal:
Genoma Bacteriano
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Proc Natl Acad Sci U S A
Ano de publicação:
2006
Tipo de documento:
Article