A multicriteria genetic algorithm to analyze microarray data
作者： M. Khabzaoui , C. Dhaenens , E.-G. Talbi
关键词: Crossover 、 Microarray analysis techniques 、 Genetic algorithm 、 Knowledge extraction 、 Optimization problem 、 Mutation (genetic algorithm) 、 Gene expression 、 Evolutionary algorithm 、 DNA microarray 、 Computer science 、 Mutation 、 Data mining 、 Gene 、 Association rule learning
摘要: Knowledge discovery from DNA microarray data has become an important research area for biologists. Association rules is task of knowledge that can be applied to the analysis gene expression in order identify patterns genes and regulatory network. may modeled as optimization problem. We propose a multicriteria model association problem present genetic algorithm designed deal with on data, obtain associations between genes. Hence, we expose main features proposed algorithm. emphasize specificities rule (encoding, mutation crossover operators) its aspects. Results are given real datasets.
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