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However, these genome-scale metabolic models must be able to first predict known <jats:italic>in vivo<\/jats:italic> phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the <jats:italic>in silico<\/jats:italic> capability in predicting <jats:italic>in vivo<\/jats:italic> phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Here we employed a systematic and iterative process, designated as Reconciling <jats:italic>In silico\/in vivo<\/jats:italic> mutaNt Growth (RING), to settle discrepancies between <jats:italic>in silico<\/jats:italic> prediction and <jats:italic>in vivo<\/jats:italic> observations to a newly reconstructed genome-scale metabolic model of the fission yeast, <jats:italic>Schizosaccharomyces pombe<\/jats:italic>, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of <jats:italic>S. pombe<\/jats:italic>. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>This study presents validation and refinement of a newly reconstructed metabolic model of the yeast <jats:italic>S. pombe<\/jats:italic>, through improving the metabolic model\u2019s predictive capabilities by reconciling the <jats:italic>in silico<\/jats:italic> predicted growth phenotypes of single-gene knockout mutants, with experimental <jats:italic>in vivo<\/jats:italic> growth data.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1752-0509-6-49","type":"journal-article","created":{"date-parts":[[2012,6,4]],"date-time":"2012-06-04T13:52:29Z","timestamp":1338817949000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico\/in vivo mutant growth"],"prefix":"10.1186","volume":"6","author":[{"given":"Seung Bum","family":"Sohn","sequence":"first","affiliation":[]},{"given":"Tae Yong","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Jay H","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Sang Yup","family":"Lee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,7,5]]},"reference":[{"key":"868_CR1","doi-asserted-by":"publisher","first-page":"7797","DOI":"10.1073\/pnas.0702609104","volume":"104","author":"JH Park","year":"2007","unstructured":"Park JH, Lee KH, Kim TY, Lee SY: Metabolic engineering of Escherichia coli for the production of L-valine based on transcriptome analysis and in silico gene knockout simulation. 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