Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified |
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Authors: | Thomas M Keane Christopher J Creevey Melissa M Pentony Thomas J Naughton James O Mclnerney |
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Affiliation: | (1) Bioinformatics Laboratory, Department of Biology, National University of Ireland, Maynooth, Co. Kildare, Ireland;(2) Bork Group, EMBL Heidelberg, Heidelberg, Germany;(3) Department of Computer Science, University College London, Gower Street, London, UK;(4) Department of Computer Science, National University of Ireland, Maynooth, Co. Kildare, Ireland |
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Abstract: | Background In recent years, model based approaches such as maximum likelihood have become the methods of choice for constructing phylogenies. A number of authors have shown the importance of using adequate substitution models in order to produce accurate phylogenies. In the past, many empirical models of amino acid substitution have been derived using a variety of different methods and protein datasets. These matrices are normally used as surrogates, rather than deriving the maximum likelihood model from the dataset being examined. With few exceptions, selection between alternative matrices has been carried out in an ad hoc manner. |
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