{"title":"图灵模式与细胞计算机。","authors":"Lewis Grozinger, Ángel Goñi-Moreno","doi":"10.1016/j.cels.2024.11.015","DOIUrl":null,"url":null,"abstract":"<p><p>Turing patterns are a key theoretical foundation for understanding organ development and organization. While they have been found to occur in natural systems, implementing new biological systems that form Turing patterns has remained challenging. To address this, Tica et al.<sup>1</sup> used synthetic genetic networks to engineer living cellular computers that successfully generate Turing patterns within growing bacterial populations.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":"15 12","pages":"1105-1106"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Turing patterns with cellular computers.\",\"authors\":\"Lewis Grozinger, Ángel Goñi-Moreno\",\"doi\":\"10.1016/j.cels.2024.11.015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Turing patterns are a key theoretical foundation for understanding organ development and organization. While they have been found to occur in natural systems, implementing new biological systems that form Turing patterns has remained challenging. To address this, Tica et al.<sup>1</sup> used synthetic genetic networks to engineer living cellular computers that successfully generate Turing patterns within growing bacterial populations.</p>\",\"PeriodicalId\":93929,\"journal\":{\"name\":\"Cell systems\",\"volume\":\"15 12\",\"pages\":\"1105-1106\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cels.2024.11.015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cels.2024.11.015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Turing patterns are a key theoretical foundation for understanding organ development and organization. While they have been found to occur in natural systems, implementing new biological systems that form Turing patterns has remained challenging. To address this, Tica et al.1 used synthetic genetic networks to engineer living cellular computers that successfully generate Turing patterns within growing bacterial populations.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
