{"title":"代谢途径双目标优化的迭代策略","authors":"Gongxian Xu","doi":"10.1109/CSO.2011.83","DOIUrl":null,"url":null,"abstract":"This paper proposes an iterative strategy to address the bi-objective optimization of metabolic pathways. The metabolic system is firstly represented by the S-system formalism. Then a weighted-sum method is used iteratively to maximize the performance of a metabolic pathway while minimizing its cost. The presented iterative strategy is applied to the fermentation pathway in Saccharomyces cerevisiae and shown to the effectiveness of the approach.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Iterative Strategy for Bi-objective Optimization of Metabolic Pathways\",\"authors\":\"Gongxian Xu\",\"doi\":\"10.1109/CSO.2011.83\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an iterative strategy to address the bi-objective optimization of metabolic pathways. The metabolic system is firstly represented by the S-system formalism. Then a weighted-sum method is used iteratively to maximize the performance of a metabolic pathway while minimizing its cost. The presented iterative strategy is applied to the fermentation pathway in Saccharomyces cerevisiae and shown to the effectiveness of the approach.\",\"PeriodicalId\":210815,\"journal\":{\"name\":\"2011 Fourth International Joint Conference on Computational Sciences and Optimization\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Fourth International Joint Conference on Computational Sciences and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSO.2011.83\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2011.83","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Iterative Strategy for Bi-objective Optimization of Metabolic Pathways
This paper proposes an iterative strategy to address the bi-objective optimization of metabolic pathways. The metabolic system is firstly represented by the S-system formalism. Then a weighted-sum method is used iteratively to maximize the performance of a metabolic pathway while minimizing its cost. The presented iterative strategy is applied to the fermentation pathway in Saccharomyces cerevisiae and shown to the effectiveness of the approach.