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Codon substitution models based on residue similarity and their applications

机译:基于残基相似度的密码子替代模型及其应用

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摘要

Codon models are now widely used to draw evolutionary inferences from alignments of homologous sequence data. Incorporating physicochemical properties of amino acids into codon models, two novel codon substitution models describing the evolution of protein-coding DNA sequences are presented based on the similarity scores of amino acids. To describe substitutions between codons a continue-time Markov process is used. Transition/transversion rate bias and nonsynonymous codon usage bias are allowed in the models. In our implementation, the parameters are estimated by maximum-likelihood (ML) method as in previous studies. Furthermore, instantaneous mutations involving more than one nucleotide position of a codon are considered in the second model. Then the two suggested models are applied to five real data sets. The analytic results indicate that the new codon models considering physicochemical properties of amino acids can provide a better fit to the data comparing with existing codon models, and then produce more reliable estimates of certain biologically important measures than existing methods.
机译:密码子模型现已广泛用于从同源序列数据的比对中得出进化推论。将氨基酸的物理化学特性整合到密码子模型中,基于氨基酸的相似性评分,提出了两种描述蛋白质编码DNA序列进化的新型密码子替代模型。为了描述密码子之间的替换,使用了持续时间的马尔可夫过程。在模型中允许过渡/转化率偏差和非同义密码子使用偏差。在我们的实现中,与以前的研究一样,通过最大似然(ML)方法估计参数。此外,在第二个模型中考虑了涉及一个密码子一个以上核苷酸位置的瞬时突变。然后,将两个建议的模型应用于五个真实数据集。分析结果表明,与现有密码子模型相比,考虑到氨基酸的理化性质的新密码子模型可以更好地拟合数据,并且比现有方法可以对某些生物学上重要的指标产生更可靠的估计。

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