The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem

BACKGROUND: This paper discusses the problem of automated annotation. It is a continuation of the previous work on the A(4)-algorithm (Adaptive algorithm of automated annotation) developed by Leontovich and others. RESULTS: A number of new statistics for the automated annotation of biological sequen...

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Detalles Bibliográficos
Autores principales: Leontovich, Andrey M, Tokmachev, Konstantin Y, van Houwelingen, Hans C
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267706/
https://www.ncbi.nlm.nih.gov/pubmed/18211675
http://dx.doi.org/10.1186/1471-2105-9-31
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author Leontovich, Andrey M
Tokmachev, Konstantin Y
van Houwelingen, Hans C
author_facet Leontovich, Andrey M
Tokmachev, Konstantin Y
van Houwelingen, Hans C
author_sort Leontovich, Andrey M
collection PubMed
description BACKGROUND: This paper discusses the problem of automated annotation. It is a continuation of the previous work on the A(4)-algorithm (Adaptive algorithm of automated annotation) developed by Leontovich and others. RESULTS: A number of new statistics for the automated annotation of biological sequences is introduced. All these statistics are based on the likelihood ratio criterion. CONCLUSION: Some of the statistics yield a prediction quality that is significantly higher (up to 1.5 times higher) in comparison with the results obtained with the A(4)-procedure.
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spelling pubmed-22677062008-05-09 The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem Leontovich, Andrey M Tokmachev, Konstantin Y van Houwelingen, Hans C BMC Bioinformatics Methodology Article BACKGROUND: This paper discusses the problem of automated annotation. It is a continuation of the previous work on the A(4)-algorithm (Adaptive algorithm of automated annotation) developed by Leontovich and others. RESULTS: A number of new statistics for the automated annotation of biological sequences is introduced. All these statistics are based on the likelihood ratio criterion. CONCLUSION: Some of the statistics yield a prediction quality that is significantly higher (up to 1.5 times higher) in comparison with the results obtained with the A(4)-procedure. BioMed Central 2008-01-22 /pmc/articles/PMC2267706/ /pubmed/18211675 http://dx.doi.org/10.1186/1471-2105-9-31 Text en Copyright © 2008 Leontovich et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Leontovich, Andrey M
Tokmachev, Konstantin Y
van Houwelingen, Hans C
The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
title The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
title_full The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
title_fullStr The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
title_full_unstemmed The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
title_short The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
title_sort comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267706/
https://www.ncbi.nlm.nih.gov/pubmed/18211675
http://dx.doi.org/10.1186/1471-2105-9-31
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