{"title":"用进化算法评价蛋白质-蛋白质相互作用网络的设计前景","authors":"P. Rakshit, Archana Chowdhury, A. Konar, A. Nagar","doi":"10.1109/NaBIC.2012.6402251","DOIUrl":null,"url":null,"abstract":"Paradigm for studying in the new biological phenomena represented by System Biology, cellular components are not considered in isolation but as forming complex networks of relationships. Protein-Protein Interaction (PPI) networks are among the first objects studied from this new point of view. The paper addresses an interesting approach to protein-protein interaction problem using Artificial Bee Colony (ABC) optimization algorithm. In this work, PPI is formulated as an optimization problem. The binding energy and mismatch in phylogenetic profiles of two bound proteins are used as a scoring function for the solutions. Results are demonstrated for three different networks both numerically and pictorially. Experimental results reveal that the proposed method outperforms Differential Evolution (DE) based PPI network design method considering the intra- and inter-molecular energies of the evolved molecules and the phylogenetic profiles of the proteins in the network.","PeriodicalId":103091,"journal":{"name":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Evaluating the designing perspective of Protein-Protein Interaction network using evolutionary algorithm\",\"authors\":\"P. Rakshit, Archana Chowdhury, A. Konar, A. Nagar\",\"doi\":\"10.1109/NaBIC.2012.6402251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Paradigm for studying in the new biological phenomena represented by System Biology, cellular components are not considered in isolation but as forming complex networks of relationships. Protein-Protein Interaction (PPI) networks are among the first objects studied from this new point of view. The paper addresses an interesting approach to protein-protein interaction problem using Artificial Bee Colony (ABC) optimization algorithm. In this work, PPI is formulated as an optimization problem. The binding energy and mismatch in phylogenetic profiles of two bound proteins are used as a scoring function for the solutions. Results are demonstrated for three different networks both numerically and pictorially. Experimental results reveal that the proposed method outperforms Differential Evolution (DE) based PPI network design method considering the intra- and inter-molecular energies of the evolved molecules and the phylogenetic profiles of the proteins in the network.\",\"PeriodicalId\":103091,\"journal\":{\"name\":\"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NaBIC.2012.6402251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NaBIC.2012.6402251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating the designing perspective of Protein-Protein Interaction network using evolutionary algorithm
Paradigm for studying in the new biological phenomena represented by System Biology, cellular components are not considered in isolation but as forming complex networks of relationships. Protein-Protein Interaction (PPI) networks are among the first objects studied from this new point of view. The paper addresses an interesting approach to protein-protein interaction problem using Artificial Bee Colony (ABC) optimization algorithm. In this work, PPI is formulated as an optimization problem. The binding energy and mismatch in phylogenetic profiles of two bound proteins are used as a scoring function for the solutions. Results are demonstrated for three different networks both numerically and pictorially. Experimental results reveal that the proposed method outperforms Differential Evolution (DE) based PPI network design method considering the intra- and inter-molecular energies of the evolved molecules and the phylogenetic profiles of the proteins in the network.