Gene-finding with the VOM model

K. O. Shohat-Zaidenraise; A. Shmilovici; I. Ben-Gal

doi:10.3233/jcm-2007-7103

Gene-finding with the VOM model

K. O. Shohat-Zaidenraise
, A. Shmilovici
, I. Ben-Gal

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

We present the architecture of an elementary gene-finding algorithm that is based on a Variable Order Markov model (VOM). The VOM model is a generalization of the traditional Markov model that can cope with varying memory dependencies. The VOM model is more efficient in terms of its parameterization and therefore can be trained on relatively short sequences. Experiments with the proposed gene-finder (GF) on three prokaryotic genomes indicate its potential advantage on the detection of short genes.

Original language	English
Pages (from-to)	45-54
Number of pages	10
Journal	Journal of Computational Methods in Sciences and Engineering
Volume	7
Issue number	1
DOIs	https://doi.org/10.3233/jcm-2007-7103
State	Published - 1 Jan 2007

Keywords

Gene finding
Variable Order Markov models
sequence analysis

ASJC Scopus subject areas

General Engineering
Computer Science Applications
Computational Mathematics

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10.3233/jcm-2007-7103

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AB - We present the architecture of an elementary gene-finding algorithm that is based on a Variable Order Markov model (VOM). The VOM model is a generalization of the traditional Markov model that can cope with varying memory dependencies. The VOM model is more efficient in terms of its parameterization and therefore can be trained on relatively short sequences. Experiments with the proposed gene-finder (GF) on three prokaryotic genomes indicate its potential advantage on the detection of short genes.

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KW - Variable Order Markov models

KW - sequence analysis

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Gene-finding with the VOM model

Abstract

Keywords

ASJC Scopus subject areas

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