MersV1, Main, Exploration, bibRecord, 001144

Metagenomic Classification Using an Abstraction Augmented Markov Model.

Identifieur interne : 001144 ( Main/Exploration ); précédent : 001143; suivant : 001145

Metagenomic Classification Using an Abstraction Augmented Markov Model.

Auteurs : Xiujun Sylvia Zhu [États-Unis] ; Monnie Mcgee [États-Unis]

Source :

Journal of computational biology : a journal of computational molecular cell biology [ 1557-8666 ] ; 2016.

RBID : pubmed:26618474

Abstract

The abstraction augmented Markov model (AAMM) is an extension of a Markov model that can be used for the analysis of genetic sequences. It is developed using the frequencies of all possible consecutive words with same length (p-mers). This article will review the theory behind AAMM and apply the theory behind AAMM in metagenomic classification.

DOI: 10.1089/cmb.2015.0141
PubMed: 26618474

Affiliations:

Le document en format XML

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Metagenomic Classification Using an Abstraction Augmented Markov Model.

Metagenomic Classification Using an Abstraction Augmented Markov Model.

Source :

Abstract

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