N. Meskin, H. Nounou, M. Nounou, A. Datta, E. Dougherty
{"title":"s系统对生物现象的干预:模型预测控制方法","authors":"N. Meskin, H. Nounou, M. Nounou, A. Datta, E. Dougherty","doi":"10.1109/ACC.2011.5990875","DOIUrl":null,"url":null,"abstract":"Recent years have witnessed extensive research activity in modeling genetic regulatory networks (GRNs) as well as in developing therapeutic intervention strategies for such networks. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of GRNs, as well as that of biochemical pathways. In this paper, an intervention strategy is proposed for the S-system model. In this approach, a model predictive control algorithm is developed which guides the target variables to their desired values. The proposed intervention strategy is applied to the glycolytic-glycogenolytic pathway as well as a generic branched pathway and the simulation results presented demonstrate the effectiveness of the proposed scheme.","PeriodicalId":225201,"journal":{"name":"Proceedings of the 2011 American Control Conference","volume":"139 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Intervention in biological phenomena modeled by S-systems: A model predictive control approach\",\"authors\":\"N. Meskin, H. Nounou, M. Nounou, A. Datta, E. Dougherty\",\"doi\":\"10.1109/ACC.2011.5990875\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent years have witnessed extensive research activity in modeling genetic regulatory networks (GRNs) as well as in developing therapeutic intervention strategies for such networks. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of GRNs, as well as that of biochemical pathways. In this paper, an intervention strategy is proposed for the S-system model. In this approach, a model predictive control algorithm is developed which guides the target variables to their desired values. The proposed intervention strategy is applied to the glycolytic-glycogenolytic pathway as well as a generic branched pathway and the simulation results presented demonstrate the effectiveness of the proposed scheme.\",\"PeriodicalId\":225201,\"journal\":{\"name\":\"Proceedings of the 2011 American Control Conference\",\"volume\":\"139 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2011 American Control Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.2011.5990875\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2011 American Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2011.5990875","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intervention in biological phenomena modeled by S-systems: A model predictive control approach
Recent years have witnessed extensive research activity in modeling genetic regulatory networks (GRNs) as well as in developing therapeutic intervention strategies for such networks. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of GRNs, as well as that of biochemical pathways. In this paper, an intervention strategy is proposed for the S-system model. In this approach, a model predictive control algorithm is developed which guides the target variables to their desired values. The proposed intervention strategy is applied to the glycolytic-glycogenolytic pathway as well as a generic branched pathway and the simulation results presented demonstrate the effectiveness of the proposed scheme.