A. Fefelov, V. Lytvynenko, M. Voronenko, S. Babichev, V. Osypenko
{"title":"克隆选择与三角差分进化混合算法重建基因调控网络","authors":"A. Fefelov, V. Lytvynenko, M. Voronenko, S. Babichev, V. Osypenko","doi":"10.1109/ELNANO.2018.8477436","DOIUrl":null,"url":null,"abstract":"One of the ways to solve the problem with identifying parameters of S-system, which is used as a model for the reconstruction of a gene regulatory network, is considered. A hybrid algorithm based on a combination of clonal selection methods and trigonometric differential evolution has been proposed. The experimental investigations of the individual parameters influence of the hybrid algorithm on a level of model errors of time series approximation of gene expression data have been carried out. The results of comparative tests with other computational methods are presented.","PeriodicalId":269665,"journal":{"name":"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Reconstruction of the Gene Regulatory Network by Hybrid Algorithm of Clonal Selection and Trigonometric Differential Evolution\",\"authors\":\"A. Fefelov, V. Lytvynenko, M. Voronenko, S. Babichev, V. Osypenko\",\"doi\":\"10.1109/ELNANO.2018.8477436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the ways to solve the problem with identifying parameters of S-system, which is used as a model for the reconstruction of a gene regulatory network, is considered. A hybrid algorithm based on a combination of clonal selection methods and trigonometric differential evolution has been proposed. The experimental investigations of the individual parameters influence of the hybrid algorithm on a level of model errors of time series approximation of gene expression data have been carried out. The results of comparative tests with other computational methods are presented.\",\"PeriodicalId\":269665,\"journal\":{\"name\":\"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELNANO.2018.8477436\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELNANO.2018.8477436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconstruction of the Gene Regulatory Network by Hybrid Algorithm of Clonal Selection and Trigonometric Differential Evolution
One of the ways to solve the problem with identifying parameters of S-system, which is used as a model for the reconstruction of a gene regulatory network, is considered. A hybrid algorithm based on a combination of clonal selection methods and trigonometric differential evolution has been proposed. The experimental investigations of the individual parameters influence of the hybrid algorithm on a level of model errors of time series approximation of gene expression data have been carried out. The results of comparative tests with other computational methods are presented.