{"oa_version":"Published Version","keyword":["Ecology","Modelling and Simulation","Computational Theory and Mathematics","Genetics","Ecology","Evolution","Behavior and Systematics","Molecular Biology","Cellular and Molecular Neuroscience"],"type":"journal_article","citation":{"ama":"Kaveh K, McAvoy A, Chatterjee K, Nowak MA. The Moran process on 2-chromatic graphs. <i>PLOS Computational Biology</i>. 2020;16(11). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008402\">10.1371/journal.pcbi.1008402</a>","ista":"Kaveh K, McAvoy A, Chatterjee K, Nowak MA. 2020. The Moran process on 2-chromatic graphs. PLOS Computational Biology. 16(11), e1008402.","chicago":"Kaveh, Kamran, Alex McAvoy, Krishnendu Chatterjee, and Martin A. Nowak. “The Moran Process on 2-Chromatic Graphs.” <i>PLOS Computational Biology</i>. Public Library of Science, 2020. <a href=\"https://doi.org/10.1371/journal.pcbi.1008402\">https://doi.org/10.1371/journal.pcbi.1008402</a>.","mla":"Kaveh, Kamran, et al. “The Moran Process on 2-Chromatic Graphs.” <i>PLOS Computational Biology</i>, vol. 16, no. 11, e1008402, Public Library of Science, 2020, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008402\">10.1371/journal.pcbi.1008402</a>.","ieee":"K. Kaveh, A. McAvoy, K. Chatterjee, and M. A. Nowak, “The Moran process on 2-chromatic graphs,” <i>PLOS Computational Biology</i>, vol. 16, no. 11. Public Library of Science, 2020.","short":"K. Kaveh, A. McAvoy, K. Chatterjee, M.A. Nowak, PLOS Computational Biology 16 (2020).","apa":"Kaveh, K., McAvoy, A., Chatterjee, K., &#38; Nowak, M. A. (2020). The Moran process on 2-chromatic graphs. <i>PLOS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1008402\">https://doi.org/10.1371/journal.pcbi.1008402</a>"},"_id":"8767","publication_identifier":{"issn":["1553-734X"],"eissn":["1553-7358"]},"doi":"10.1371/journal.pcbi.1008402","month":"11","title":"The Moran process on 2-chromatic graphs","issue":"11","publication_status":"published","publisher":"Public Library of Science","oa":1,"scopus_import":"1","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","department":[{"_id":"KrCh"}],"file_date_updated":"2020-11-18T07:26:10Z","language":[{"iso":"eng"}],"author":[{"first_name":"Kamran","full_name":"Kaveh, Kamran","last_name":"Kaveh"},{"last_name":"McAvoy","full_name":"McAvoy, Alex","first_name":"Alex"},{"orcid":"0000-0002-4561-241X","first_name":"Krishnendu","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Martin A.","full_name":"Nowak, Martin A.","last_name":"Nowak"}],"file":[{"creator":"dernst","checksum":"555456dd0e47bcf9e0994bcb95577e88","success":1,"access_level":"open_access","file_id":"8768","relation":"main_file","file_name":"2020_PlosCompBio_Kaveh.pdf","date_created":"2020-11-18T07:26:10Z","file_size":2498594,"date_updated":"2020-11-18T07:26:10Z","content_type":"application/pdf"}],"ddc":["000"],"year":"2020","article_processing_charge":"No","date_published":"2020-11-05T00:00:00Z","publication":"PLOS Computational Biology","article_number":"e1008402","date_created":"2020-11-18T07:20:23Z","article_type":"original","has_accepted_license":"1","external_id":{"isi":["000591317200004"]},"volume":16,"isi":1,"acknowledgement":"We thank Igor Erovenko for many helpful comments on an earlier version of this paper. : Army Research Laboratory (grant W911NF-18-2-0265) (M.A.N.); the Bill & Melinda Gates Foundation (grant OPP1148627) (M.A.N.); the NVIDIA Corporation (A.M.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","day":"05","quality_controlled":"1","intvolume":"        16","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"date_updated":"2023-08-22T12:49:18Z","status":"public","abstract":[{"text":"Resources are rarely distributed uniformly within a population. Heterogeneity in the concentration of a drug, the quality of breeding sites, or wealth can all affect evolutionary dynamics. In this study, we represent a collection of properties affecting the fitness at a given location using a color. A green node is rich in resources while a red node is poorer. More colors can represent a broader spectrum of resource qualities. For a population evolving according to the birth-death Moran model, the first question we address is which structures, identified by graph connectivity and graph coloring, are evolutionarily equivalent. We prove that all properly two-colored, undirected, regular graphs are evolutionarily equivalent (where “properly colored” means that no two neighbors have the same color). We then compare the effects of background heterogeneity on properly two-colored graphs to those with alternative schemes in which the colors are permuted. Finally, we discuss dynamic coloring as a model for spatiotemporal resource fluctuations, and we illustrate that random dynamic colorings often diminish the effects of background heterogeneity relative to a proper two-coloring.","lang":"eng"}]}