Efficient context-dependent model building based on clustering posterior distributions for non-coding sequences |
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Authors: | Guy Baele Yves Van de Peer Stijn Vansteelandt |
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Institution: | (1) Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 S9, B-9000 Ghent, Belgium;(2) Department of Plant Systems Biology, VIB, B-9052 Ghent, Belgium;(3) Bioinformatics and Evolutionary Genomics, Department of Molecular Genetics, Ghent University, B-9052 Ghent, Belgium |
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Abstract: | Background Many recent studies that relax the assumption of independent evolution of sites have done so at the expense of a drastic increase
in the number of substitution parameters. While additional parameters cannot be avoided to model context-dependent evolution,
a large increase in model dimensionality is only justified when accompanied with careful model-building strategies that guard
against overfitting. An increased dimensionality leads to increases in numerical computations of the models, increased convergence
times in Bayesian Markov chain Monte Carlo algorithms and even more tedious Bayes Factor calculations. |
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