Junfeng Liu, Liang Chen, Hongyu Zhao, Dirk F Moore, Yong Lin, Weichung Joe Shih
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引用次数: 0
Abstract
Probabilistic DNA sequence models have been intensively applied to genome research. Within the evolutionary biology framework, this article investigates the feasibility for rigorously estimating the probability of a set of orthologous DNA sequences which evolve from a common progenitor. We propose Monte Carlo integration algorithms to sample the unknown ancestral and/or root sequences a posteriori conditional on a reference sequence and apply pairwise Needleman-Wunsch alignment between the sampled and nonreference species sequences to estimate the probability. We test our algorithms on both simulated and real sequences and compare calculated probabilities from Monte Carlo integration to those induced by single multiple alignment.
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