Phase transitions of the Moran process and algorithmic consequences
The Moran process is a random process that models the spread of genetic mutations through graphs. On connected graphs, the process eventually reaches “fixation,” where all vertices are mutants, or “extinction,” where none are. Our main result is an almost‐tight upper bound on expected absorption tim...
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Veröffentlicht in: | Random structures & algorithms 2020-05, Vol.56 (3), p.597-647 |
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description | The Moran process is a random process that models the spread of genetic mutations through graphs. On connected graphs, the process eventually reaches “fixation,” where all vertices are mutants, or “extinction,” where none are. Our main result is an almost‐tight upper bound on expected absorption time. For all ϵ>0, we show that the expected absorption time on an n‐vertex graph is o(n3+ϵ). Specifically, it is at most n3eO((loglogn)3), and there is a family of graphs where it is Ω(n3). In proving this, we establish a phase transition in the probability of fixation, depending on the mutants' fitness r. We show that no similar phase transition occurs for digraphs, where it is already known that the expected absorption time can be exponential. Finally, we give an improved fully polynomial randomized approximation scheme (FPRAS) for approximating the probability of fixation. On degree‐bounded graphs where some basic properties are given, its running time is independent of the number of vertices. |
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On degree‐bounded graphs where some basic properties are given, its running time is independent of the number of vertices.</description><subject>Absorption</subject><subject>absorption time</subject><subject>Apexes</subject><subject>evolutionary dynamics</subject><subject>Fixation</subject><subject>fixation probability</subject><subject>Graph theory</subject><subject>Graphs</subject><subject>Moran process</subject><subject>Mutation</subject><subject>Phase transitions</subject><subject>Polynomials</subject><subject>Random processes</subject><subject>Upper bounds</subject><issn>1042-9832</issn><issn>1098-2418</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kMtOwzAQRS0EEqWw4A8ssWKR1o8ktpdVBAWpCMRjbdnOhKRq42KnQv17XMKW1Yzmnpk7ughdUzKjhLB5iGbGiFTkBE0oUTJjOZWnxz5nmZKcnaOLGNeEEMEZn6DqpTUR8BBMH7uh833EvsFDC_jJpxneBe8gRmz6GpvNpw_d0G47h10i4WsPfVIv0VljNhGu_uoUfdzfvVcP2ep5-VgtVpnjnJFMFslT5iVQAYrWpZG1snVBlGjAUstKYmtZM7DOcKXACVo2jQCbA-M2sXyKbsa76alkHQe99vvQJ0vNuJBUiUIVibodKRd8jAEavQvd1oSDpkQfM9IpI_2bUWLnI_vdbeDwP6hf3xbjxg-NDGig</recordid><startdate>202005</startdate><enddate>202005</enddate><creator>Goldberg, Leslie</creator><creator>Lapinskas, John</creator><creator>Richerby, David</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>202005</creationdate><title>Phase transitions of the Moran process and algorithmic consequences</title><author>Goldberg, Leslie ; Lapinskas, John ; Richerby, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3320-85073846e17e91d6a8d9bd5097feb1b260bd8d2ebca399ec716ff7eb4e23b8d93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Absorption</topic><topic>absorption time</topic><topic>Apexes</topic><topic>evolutionary dynamics</topic><topic>Fixation</topic><topic>fixation probability</topic><topic>Graph theory</topic><topic>Graphs</topic><topic>Moran process</topic><topic>Mutation</topic><topic>Phase transitions</topic><topic>Polynomials</topic><topic>Random processes</topic><topic>Upper bounds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Goldberg, Leslie</creatorcontrib><creatorcontrib>Lapinskas, John</creatorcontrib><creatorcontrib>Richerby, David</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Random structures & algorithms</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Goldberg, Leslie</au><au>Lapinskas, John</au><au>Richerby, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Phase transitions of the Moran process and algorithmic consequences</atitle><jtitle>Random structures & algorithms</jtitle><date>2020-05</date><risdate>2020</risdate><volume>56</volume><issue>3</issue><spage>597</spage><epage>647</epage><pages>597-647</pages><issn>1042-9832</issn><eissn>1098-2418</eissn><abstract>The Moran process is a random process that models the spread of genetic mutations through graphs. On connected graphs, the process eventually reaches “fixation,” where all vertices are mutants, or “extinction,” where none are. Our main result is an almost‐tight upper bound on expected absorption time. For all ϵ>0, we show that the expected absorption time on an n‐vertex graph is o(n3+ϵ). Specifically, it is at most n3eO((loglogn)3), and there is a family of graphs where it is Ω(n3). In proving this, we establish a phase transition in the probability of fixation, depending on the mutants' fitness r. We show that no similar phase transition occurs for digraphs, where it is already known that the expected absorption time can be exponential. Finally, we give an improved fully polynomial randomized approximation scheme (FPRAS) for approximating the probability of fixation. 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subjects | Absorption absorption time Apexes evolutionary dynamics Fixation fixation probability Graph theory Graphs Moran process Mutation Phase transitions Polynomials Random processes Upper bounds |
title | Phase transitions of the Moran process and algorithmic consequences |
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