Fast multiple alignment of ungapped DNA sequences using information theory and a relaxation method
Discrete Applied Mathematics - Special volume on computational molecular biology
An improved collapsed Gibbs sampler for Dirichlet process mixing models
Computational Statistics & Data Analysis
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The way for performing multiple sequence alignment is based on the criterion of the maximum scored information content computed from a weight matrix, but it is possible to have two or more alignments to have the same highest score leading to ambiguities in selecting the best alignment. This paper addresses this issue by introducing the concept of joint weight matrix to eliminate the randomness in selecting the best alignment of multiple sequences. Alignments with equal scores are iteratively re-scored with joint weight matrix of increasing level (nucleotide pairs, triplets and so on) until one single best alignment is eventually found. This method can be easily implemented to algorithms using weight matrix for scoring such as those based on the widely used Gibbs sampling method.