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Investigating selection on viruses: a statistical alignment approach
2008
BMC Bioinformatics
Two problems complicate the study of selection in viral genomes: Firstly, the presence of genes in overlapping reading frames implies that selection in one reading frame can bias our estimates of neutral mutation rates in another reading frame. Secondly, the high mutation rates we are likely to encounter complicate the inference of a reliable alignment of genomes. To address these issues, we develop a model that explicitly models selection in overlapping reading frames. We then integrate this
doi:10.1186/1471-2105-9-304
pmid:18616801
pmcid:PMC2478691
fatcat:phcsdjs2wbaorhetvhuwl344nm