Beyond similarity assessment: selecting the optimal model for sequence alignment via the Factorized Asymptotic Bayesian algorithm
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DOI: 10.1093/bioinformatics/btx643
Abstract: Abstract Motivation Pair Hidden Markov Models (PHMMs) are probabilistic models used for pairwise sequence alignment, a quintessential problem in bioinformatics. PHMMs include three types of hidden states: match, insertion and deletion. Most previous studies have… read more here.
Keywords: hidden states; beyond similarity; similarity assessment; sequence alignment ... See more keywords