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- W2107459209 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." @default.
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- W2107459209 date "2006-11-14" @default.
- W2107459209 modified "2023-10-16" @default.
- W2107459209 title "Systems approach to refining genome annotation" @default.
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- W2107459209 doi "https://doi.org/10.1073/pnas.0603364103" @default.
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