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Genome-Scale Classification of Recombinant and Non-Recombinant HIV-1 Sequences Using Artificial Neural Network Ensembles
2016
Current Science
Genetic recombination and high rate of mutations in the HIV-1 genome increase the diversity of HIV-1, which allows viruses to escape more easily from host immune system or develop resistance for antiretroviral drugs. Consequently, it is indispensable to devise an effective method for recognition of recombination in HIV-1 strains. This article presents ensemble models of artificial neural network for the classification of recombinant and non-recombinant sequences of HIV-1 genome. We have
doi:10.18520/cs/v111/i5/853-860
fatcat:yyv6kkg3kzgwdlu6lafrqpzcqe