--- res: bibo_abstract: - "The solution space of genome-scale models of cellular metabolism provides a map between physically\r\nviable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the\r\ncorresponding growth rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat empirical growth rate distributions recently obtained in experiments at single-cell resolution can\r\nbe explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of\r\na large bacterial population that captures this trade-off. The scaling relationships observed in\r\nexperiments encode, in such frameworks, for the same distance from the maximum achievable growth\r\nrate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions, these results allow for multiple\r\nimplications and extensions in spite of the underlying conceptual simplicity.@eng" bibo_authorlist: - foaf_Person: foaf_givenName: Daniele foaf_name: De Martino, Daniele foaf_surname: De Martino foaf_workInfoHomepage: http://www.librecat.org/personId=3FF5848A-F248-11E8-B48F-1D18A9856A87 orcid: 0000-0002-5214-4706 - foaf_Person: foaf_givenName: Fabrizio foaf_name: Capuani, Fabrizio foaf_surname: Capuani - foaf_Person: foaf_givenName: Andrea foaf_name: De Martino, Andrea foaf_surname: De Martino bibo_doi: 10.1088/1478-3975/13/3/036005 bibo_issue: '3' bibo_volume: 13 dct_date: 2016^xs_gYear dct_language: eng dct_publisher: IOP Publishing Ltd.@ dct_title: 'Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli@' ...