Whole genome/proteome based phylogeny reconstruction for prokaryotes using higher order Markov model and chaos game representation.
Mol Phylogenet Evol
; 96: 102-111, 2016 Mar.
Article
em En
| MEDLINE
| ID: mdl-26724405
ABSTRACT
UNLABELLED Traditional methods for sequence comparison and phylogeny reconstruction rely on pair wise and multiple sequence alignments. But alignment could not be directly applied to whole genome/proteome comparison and phylogenomic studies due to their high computational complexity. Hence alignment-free methods became popular in recent years. Here we propose a fast alignment-free method for whole genome/proteome comparison and phylogeny reconstruction using higher order Markov model and chaos game representation. In the present method, we use the transition matrices of higher order Markov models to characterize amino acid or DNA sequences for their comparison. The order of the Markov model is uniquely identified by maximizing the average Shannon entropy of conditional probability distributions. Using one-dimensional chaos game representation and linked list, this method can reduce large memory and time consumption which is due to the large-scale conditional probability distributions. To illustrate the effectiveness of our method, we employ it for fast phylogeny reconstruction based on genome/proteome sequences of two species data sets used in previous published papers. Our results demonstrate that the present method is useful and efficient. AVAILABILITY AND IMPLEMENTATION The source codes for our algorithm to get the distance matrix and genome/proteome sequences can be downloaded from ftp//121.199.20.25/. The software Phylip and EvolView we used to construct phylogenetic trees can be referred from their websites.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Filogenia
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Células Procarióticas
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Cadeias de Markov
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Genoma
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Dinâmica não Linear
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Proteoma
Tipo de estudo:
Health_economic_evaluation
Idioma:
En
Revista:
Mol Phylogenet Evol
Assunto da revista:
BIOLOGIA
/
BIOLOGIA MOLECULAR
Ano de publicação:
2016
Tipo de documento:
Article