期刊
GENE
卷 347, 期 2, 页码 207-217出版社
ELSEVIER
DOI: 10.1016/j.gene.2004.12.011
关键词
protein evolution; phylogenetics; Bayesian Markov chain Monte Carlo; statistical potentials
Standard likelihood-based frameworks in phylogenetics consider the process of evolution of a sequence site by site. Assuming that sites evolve independently greatly simplifies the required calculations. However, this simplification is known to be incorrect in many cases. Here, a computational method that allows for general dependence between sites of a sequence is investigated. Using this method, measures acting as sequence fitness proxies can be considered over a phylogenetic tree. In this work, a set of statistically derived amino acid pairwise potentials, developed in the context of protein threading, is used to account for what we call the structural fitness of a sequence. We describe a model combining statistical potentials with an empirical amino acid substitution matrix. We propose such a combination as a useful way of capturing the complexity of protein evolution. Finally, we outline features of the model using three datasets and show the approach's sensitivity to different tree topologies. (c) 2004 Elsevier B.V. All rights reserved.
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