Automatic Spot Addressing in cDNA Microarray Images

Autores
Larese, Mónica G.; Gómez, Juan Carlos
Año de publicación
2007
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Complementary DNA (cDNA) microarrays are a powerful high throughput technology developed in the last decade allowing researchers to analyze the behaviour and interaction of thousands of genes simultaneously. The large amount of information provided by microarray images requires automatic techniques to develop accurate and ef cient processing. Each spot in the microarray contains the hybridization level of a single gene. One of the most important features of these images are the regularity and pseudo-periodicity implicit in the spot arrangement. In this paper, an automatic approach based on texture analysis techniques is proposed to localize spots in microarray images. The method estimates the displacement vectors which characterize the texture (i.e. the spot arrangement). This is achieved by means of applying the generalized Hough transform on the 2D autocorrelation function previously segmented via morphological operations. The obtained displacement vectors are used to generate a grid template which is matched to the original image. The root mean square error between the estimated locations and the ones computed via a semiautomatic tool is computed to evaluate the accuracy of the process. The method yields promising results with low errors.
V Workshop de Computación Gráfica, Imágenes Y Visualización
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Informática
bioinformatics
cDNA microarrays
image analysis
automatic addressing
Image Representation
Bioingeniería
Image displays
Logic arrays
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22311

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network_name_str SEDICI (UNLP)
spelling Automatic Spot Addressing in cDNA Microarray ImagesLarese, Mónica G.Gómez, Juan CarlosCiencias InformáticasInformáticabioinformaticscDNA microarraysimage analysisautomatic addressingImage RepresentationBioingenieríaImage displaysLogic arraysComplementary DNA (cDNA) microarrays are a powerful high throughput technology developed in the last decade allowing researchers to analyze the behaviour and interaction of thousands of genes simultaneously. The large amount of information provided by microarray images requires automatic techniques to develop accurate and ef cient processing. Each spot in the microarray contains the hybridization level of a single gene. One of the most important features of these images are the regularity and pseudo-periodicity implicit in the spot arrangement. In this paper, an automatic approach based on texture analysis techniques is proposed to localize spots in microarray images. The method estimates the displacement vectors which characterize the texture (i.e. the spot arrangement). This is achieved by means of applying the generalized Hough transform on the 2D autocorrelation function previously segmented via morphological operations. The obtained displacement vectors are used to generate a grid template which is matched to the original image. The root mean square error between the estimated locations and the ones computed via a semiautomatic tool is computed to evaluate the accuracy of the process. The method yields promising results with low errors.V Workshop de Computación Gráfica, Imágenes Y VisualizaciónRed de Universidades con Carreras en Informática (RedUNCI)2007info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf677-688http://sedici.unlp.edu.ar/handle/10915/22311enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:36:33Zoai:sedici.unlp.edu.ar:10915/22311Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:36:33.311SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Automatic Spot Addressing in cDNA Microarray Images
title Automatic Spot Addressing in cDNA Microarray Images
spellingShingle Automatic Spot Addressing in cDNA Microarray Images
Larese, Mónica G.
Ciencias Informáticas
Informática
bioinformatics
cDNA microarrays
image analysis
automatic addressing
Image Representation
Bioingeniería
Image displays
Logic arrays
title_short Automatic Spot Addressing in cDNA Microarray Images
title_full Automatic Spot Addressing in cDNA Microarray Images
title_fullStr Automatic Spot Addressing in cDNA Microarray Images
title_full_unstemmed Automatic Spot Addressing in cDNA Microarray Images
title_sort Automatic Spot Addressing in cDNA Microarray Images
dc.creator.none.fl_str_mv Larese, Mónica G.
Gómez, Juan Carlos
author Larese, Mónica G.
author_facet Larese, Mónica G.
Gómez, Juan Carlos
author_role author
author2 Gómez, Juan Carlos
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Informática
bioinformatics
cDNA microarrays
image analysis
automatic addressing
Image Representation
Bioingeniería
Image displays
Logic arrays
topic Ciencias Informáticas
Informática
bioinformatics
cDNA microarrays
image analysis
automatic addressing
Image Representation
Bioingeniería
Image displays
Logic arrays
dc.description.none.fl_txt_mv Complementary DNA (cDNA) microarrays are a powerful high throughput technology developed in the last decade allowing researchers to analyze the behaviour and interaction of thousands of genes simultaneously. The large amount of information provided by microarray images requires automatic techniques to develop accurate and ef cient processing. Each spot in the microarray contains the hybridization level of a single gene. One of the most important features of these images are the regularity and pseudo-periodicity implicit in the spot arrangement. In this paper, an automatic approach based on texture analysis techniques is proposed to localize spots in microarray images. The method estimates the displacement vectors which characterize the texture (i.e. the spot arrangement). This is achieved by means of applying the generalized Hough transform on the 2D autocorrelation function previously segmented via morphological operations. The obtained displacement vectors are used to generate a grid template which is matched to the original image. The root mean square error between the estimated locations and the ones computed via a semiautomatic tool is computed to evaluate the accuracy of the process. The method yields promising results with low errors.
V Workshop de Computación Gráfica, Imágenes Y Visualización
Red de Universidades con Carreras en Informática (RedUNCI)
description Complementary DNA (cDNA) microarrays are a powerful high throughput technology developed in the last decade allowing researchers to analyze the behaviour and interaction of thousands of genes simultaneously. The large amount of information provided by microarray images requires automatic techniques to develop accurate and ef cient processing. Each spot in the microarray contains the hybridization level of a single gene. One of the most important features of these images are the regularity and pseudo-periodicity implicit in the spot arrangement. In this paper, an automatic approach based on texture analysis techniques is proposed to localize spots in microarray images. The method estimates the displacement vectors which characterize the texture (i.e. the spot arrangement). This is achieved by means of applying the generalized Hough transform on the 2D autocorrelation function previously segmented via morphological operations. The obtained displacement vectors are used to generate a grid template which is matched to the original image. The root mean square error between the estimated locations and the ones computed via a semiautomatic tool is computed to evaluate the accuracy of the process. The method yields promising results with low errors.
publishDate 2007
dc.date.none.fl_str_mv 2007
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/22311
url http://sedici.unlp.edu.ar/handle/10915/22311
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
677-688
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instname:Universidad Nacional de La Plata
instacron:UNLP
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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