Kiyoshi Ezawa

This paper develops a theoretical framework for calculating sequence alignment probabilities under a general continuous-time Markov model of insertions and deletions using perturbation theory.

The paper develops an algorithm to approximate the probability of local multiple sequence alignments using a perturbative formulation of a continuous-time Markov model of indels, showing it works well for moderate gap and branch lengths.

This paper applies an ab initio perturbative formulation to calculate alignment probabilities under indel models, showing that fewest-indel terms can accurately approximate local alignment probabilities under modest conditions.

This paper extends a perturbative formulation of a continuous-time Markov model of sequence evolution to include substitutions and other mutations like genomic rearrangements.