Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)

Background Molecular mechanisms of plant-pathogen interactions have been studied thoroughly but much about them is still unknown. A better understanding of these mechanisms and the detection of new resistance genes can improve crop production and food supply. Extracting this knowledge from available...

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Autores principales:	Torres-Avilés,Francisco, Romeo,José S, López-Kleine,Liliana
Lenguaje:	English
Publicado:	Pontificia Universidad Católica de Valparaíso 2014
Materias:	Classification Data mining Functional gene prediction GEE models Gene expression data Plant immunity genes
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582014000200004
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spelling	oai:scielo:S0717-345820140002000042014-09-02Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)Torres-Avilés,FranciscoRomeo,José SLópez-Kleine,Liliana Classification Data mining Functional gene prediction GEE models Gene expression data Plant immunity genes Background Molecular mechanisms of plant-pathogen interactions have been studied thoroughly but much about them is still unknown. A better understanding of these mechanisms and the detection of new resistance genes can improve crop production and food supply. Extracting this knowledge from available genomic data is a challenging task. Results Here, we evaluate the usefulness of clustering, data-mining and regression to identify potential new resistance genes. Three types of analyses were conducted separately over two conditions, tomatoes inoculated with Phytophthora infestans and not inoculated tomatoes. Predictions for 10 new resistance genes obtained by all applied methods were selected as being the most reliable and are therefore reported as potential resistance genes. Conclusion Application of different statistical analyses to detect potential resistance genes reliably has shown to conduct interesting results that improve knowledge on molecular mechanisms of plant resistance to pathogens.info:eu-repo/semantics/openAccessPontificia Universidad Católica de ValparaísoElectronic Journal of Biotechnology v.17 n.2 20142014-03-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582014000200004en10.1016/j.ejbt.2014.01.003
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Classification Data mining Functional gene prediction GEE models Gene expression data Plant immunity genes
spellingShingle	Classification Data mining Functional gene prediction GEE models Gene expression data Plant immunity genes Torres-Avilés,Francisco Romeo,José S López-Kleine,Liliana Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)
description	Background Molecular mechanisms of plant-pathogen interactions have been studied thoroughly but much about them is still unknown. A better understanding of these mechanisms and the detection of new resistance genes can improve crop production and food supply. Extracting this knowledge from available genomic data is a challenging task. Results Here, we evaluate the usefulness of clustering, data-mining and regression to identify potential new resistance genes. Three types of analyses were conducted separately over two conditions, tomatoes inoculated with Phytophthora infestans and not inoculated tomatoes. Predictions for 10 new resistance genes obtained by all applied methods were selected as being the most reliable and are therefore reported as potential resistance genes. Conclusion Application of different statistical analyses to detect potential resistance genes reliably has shown to conduct interesting results that improve knowledge on molecular mechanisms of plant resistance to pathogens.
author	Torres-Avilés,Francisco Romeo,José S López-Kleine,Liliana
author_facet	Torres-Avilés,Francisco Romeo,José S López-Kleine,Liliana
author_sort	Torres-Avilés,Francisco
title	Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)
title_short	Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)
title_full	Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)
title_fullStr	Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)
title_full_unstemmed	Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)
title_sort	data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (solanum lycopersicum)
publisher	Pontificia Universidad Católica de Valparaíso
publishDate	2014
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582014000200004
work_keys_str_mv	AT torresavilesfrancisco dataminingandinfluentialanalysisofgeneexpressiondataforplantresistancegeneidentificationintomatosolanumlycopersicum AT romeojoses dataminingandinfluentialanalysisofgeneexpressiondataforplantresistancegeneidentificationintomatosolanumlycopersicum AT lopezkleineliliana dataminingandinfluentialanalysisofgeneexpressiondataforplantresistancegeneidentificationintomatosolanumlycopersicum
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Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)

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