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Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors

To identify divergent seven-transmembrane receptor (7TMR) candidates from the Arabidopsis thaliana genome, multiple protein classification methods were combined, including both alignment-based and alignment-free classifiers. This resolved problems in optimally training individual classifiers using l...

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Autores principales: Moriyama, Etsuko N, Strope, Pooja K, Opiyo, Stephen O, Chen, Zhongying, Jones, Alan M
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1794564/
https://www.ncbi.nlm.nih.gov/pubmed/17064408
http://dx.doi.org/10.1186/gb-2006-7-10-r96
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author Moriyama, Etsuko N
Strope, Pooja K
Opiyo, Stephen O
Chen, Zhongying
Jones, Alan M
author_facet Moriyama, Etsuko N
Strope, Pooja K
Opiyo, Stephen O
Chen, Zhongying
Jones, Alan M
author_sort Moriyama, Etsuko N
collection PubMed
description To identify divergent seven-transmembrane receptor (7TMR) candidates from the Arabidopsis thaliana genome, multiple protein classification methods were combined, including both alignment-based and alignment-free classifiers. This resolved problems in optimally training individual classifiers using limited and divergent samples, and increased stringency for candidate proteins. We identified 394 proteins as 7TMR candidates and highlighted 54 with corresponding expression patterns for further investigation.
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spelling pubmed-17945642007-02-08 Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors Moriyama, Etsuko N Strope, Pooja K Opiyo, Stephen O Chen, Zhongying Jones, Alan M Genome Biol Method To identify divergent seven-transmembrane receptor (7TMR) candidates from the Arabidopsis thaliana genome, multiple protein classification methods were combined, including both alignment-based and alignment-free classifiers. This resolved problems in optimally training individual classifiers using limited and divergent samples, and increased stringency for candidate proteins. We identified 394 proteins as 7TMR candidates and highlighted 54 with corresponding expression patterns for further investigation. BioMed Central 2006 2006-10-25 /pmc/articles/PMC1794564/ /pubmed/17064408 http://dx.doi.org/10.1186/gb-2006-7-10-r96 Text en Copyright © 2006 Moriyama 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 Method
Moriyama, Etsuko N
Strope, Pooja K
Opiyo, Stephen O
Chen, Zhongying
Jones, Alan M
Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
title Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
title_full Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
title_fullStr Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
title_full_unstemmed Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
title_short Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
title_sort mining the arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1794564/
https://www.ncbi.nlm.nih.gov/pubmed/17064408
http://dx.doi.org/10.1186/gb-2006-7-10-r96
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