中文摘要：

考虑不同氨基酸间置换率的差异性,构建了两个基于氨基酸相似性的密码子模型.利用连续时间的马尔可夫过程和最大似然法,将新模型应用到三个真实的数据集.通过数值实验分析结果显示,新模型比现有模型对数据集有更好的适用性,且能给出更可靠的参数估计值.

英文摘要：

To address the heterogeneity of amino acids＇ displacement ratio,we develop two new codon models based on the similarity of amino acids.The new models were applied to three real datasets by a continuous-time Markov process and the maximum likelihood method.The analytic results show that,compared with the current codon model,the new similarity-based codon models are of a better adaptability to the dataset and can produce more reliable estimated values of parameters.