无比对参数估计的分子进化随机置换-插入-缺失（RSID）模型
Random Substitution-Insertion-Deletion (RSID) Model of Molecular Evolution with Alignment-free Parameter Estimation
摘要：
我们提出了一个全面的新框架，用于处理生物学上精确的分子进化模型。该模型提供了一个系统的框架，研究模型的分子进化，实现异构率，阅读框的保护，不同的插入和删除率，可定制的参数化的概率和类型的取代，插入，删除，以及相邻的依赖关系。我们已经说明了一个无限状态马尔可夫链的模型，以最大限度地提高适用定理的数量在模型的分析有用。我们使用这样的定理来开发一个无干扰的参数估计技术。这种无干扰技术规避了许多与干扰依赖估计相关的细微问题。然后，我们应用我们的模型的实现再现（以完全无干扰的方式）Zhang和Gerstein（2003）关于人类核糖体蛋白假基因中indel长度分布的一些观察结果。
英文摘要：
We present a comprehensive new framework for handling biologically accurate models of molecular evolution. This model provides a systematic framework for studying models of molecular evolution that implement heterogeneous rates, conservation of reading frame, differing rates of insertion and deletion, customizable parametrization of the probabilities and types of substitutions, insertions, and deletions, as well as neighboring dependencies. We have stated the model in terms of an infinite state Markov chain in order to maximize the number of applicable theorems useful in the analysis of the model. We use such theorems to develop an alignment-free parameter estimation technique. This alignment-free technique circumvents many of the nuanced issues related to alignment-dependent estimation. We then apply an implementation of our model to reproduce (in a completely alignment-free fashion) some observed results of Zhang and Gerstein (2003) regarding indel length distribution in human ribosomal protein pseudogenes.
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