{"doi":"10.1088/1742-5468/aa4e8f","author":[{"id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","last_name":"De Martino","orcid":"0000-0002-5214-4706","first_name":"Daniele","full_name":"De Martino, Daniele"},{"first_name":"Davide","full_name":"Masoero, Davide","last_name":"Masoero"}],"_id":"1188","publication":" Journal of Statistical Mechanics: Theory and Experiment","publication_status":"published","article_number":"123502","abstract":[{"text":"We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. \r\nIn the asymptotic regime of slow\r\ndiffusion, that coincides with the relevant experimental range, the resulting\r\nnon-linear Fokker–Planck equation is solved for the steady state in the WKB\r\napproximation that maps it into the ground state of a quantum particle in an\r\nAiry potential plus a centrifugal term. We retrieve scaling laws for growth rate\r\nfluctuations and time response with respect to the distance from the maximum\r\ngrowth rate suggesting that suboptimal populations can have a faster response\r\nto perturbations.","lang":"eng"}],"volume":2016,"date_updated":"2021-01-12T06:48:57Z","type":"journal_article","status":"public","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa":1,"acknowledgement":"D De Martino is supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. D Masoero is supported by the FCT scholarship, number SFRH/BPD/75908/2011. D De Martino thanks the Grupo de Física Matemática of the Universidade de Lisboa for the kind hospitality. We also wish to thank Matteo Osella, Vincenzo Vitagliano and Vera Luz Masoero for useful discussions, also late at night.","department":[{"_id":"GaTk"}],"citation":{"mla":"De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism &#38;amp; Growth.” <i> Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2016, no. 12, 123502, IOPscience, 2016, doi:<a href=\"https://doi.org/10.1088/1742-5468/aa4e8f\">10.1088/1742-5468/aa4e8f</a>.","ama":"De Martino D, Masoero D. Asymptotic analysis of noisy fitness maximization, applied to metabolism &#38;amp; growth. <i> Journal of Statistical Mechanics: Theory and Experiment</i>. 2016;2016(12). doi:<a href=\"https://doi.org/10.1088/1742-5468/aa4e8f\">10.1088/1742-5468/aa4e8f</a>","short":"D. De Martino, D. Masoero,  Journal of Statistical Mechanics: Theory and Experiment 2016 (2016).","ieee":"D. De Martino and D. Masoero, “Asymptotic analysis of noisy fitness maximization, applied to metabolism &#38;amp; growth,” <i> Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2016, no. 12. IOPscience, 2016.","chicago":"De Martino, Daniele, and Davide Masoero. “Asymptotic Analysis of Noisy Fitness Maximization, Applied to Metabolism &#38;amp; Growth.” <i> Journal of Statistical Mechanics: Theory and Experiment</i>. IOPscience, 2016. <a href=\"https://doi.org/10.1088/1742-5468/aa4e8f\">https://doi.org/10.1088/1742-5468/aa4e8f</a>.","ista":"De Martino D, Masoero D. 2016. Asymptotic analysis of noisy fitness maximization, applied to metabolism &#38;amp; growth.  Journal of Statistical Mechanics: Theory and Experiment. 2016(12), 123502.","apa":"De Martino, D., &#38; Masoero, D. (2016). Asymptotic analysis of noisy fitness maximization, applied to metabolism &#38;amp; growth. <i> Journal of Statistical Mechanics: Theory and Experiment</i>. IOPscience. <a href=\"https://doi.org/10.1088/1742-5468/aa4e8f\">https://doi.org/10.1088/1742-5468/aa4e8f</a>"},"date_created":"2018-12-11T11:50:37Z","month":"12","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1606.09048"}],"title":"Asymptotic analysis of noisy fitness maximization, applied to metabolism &amp; growth","scopus_import":1,"quality_controlled":"1","issue":"12","oa_version":"Preprint","publist_id":"6165","intvolume":"      2016","language":[{"iso":"eng"}],"ec_funded":1,"year":"2016","publisher":"IOPscience","day":"30","date_published":"2016-12-30T00:00:00Z"}