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We present a comprehensive new framework for handling biologically accuratemodels of molecular evolution. This model provides a systematic framework forstudying 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 statedthe model in terms of an infinite state Markov chain in order to maximize thenumber of applicable theorems useful in the analysis of the model. We use suchtheorems to develop an alignment-free parameter estimation technique. Thisalignment-free technique circumvents many of the nuanced issues related toalignment-dependent estimation. We then apply an implementation of our model toreproduce (in a completely alignment-free fashion) some observed results ofZhang and Gerstein (2003) regarding indel length distribution in humanribosomal protein pseudogenes.

Random Substitution-Insertion-Deletion (RSID) Model of Molecular Evolution with Alignment-free Parameter Estimation