Automatic Spot Adressing in cDNA Microarray Images
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...
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Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
2008-07-01
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doaj-95f1c4c7224b4272814642ac58f7762c2021-05-05T13:58:16ZengPostgraduate Office, School of Computer Science, Universidad Nacional de La PlataJournal of Computer Science and Technology1666-60461666-60382008-07-018026470437Automatic Spot Adressing in cDNA Microarray ImagesMónica G. Larese0Juan Carlos Gómez1Centro Intern. Franco-Argentino de Cs. de la Inform. y de Sist. ( CIFASIS-CONICET), Rosario, ArgentinaLaboratory for System Dynamics and Signal Processing, FCEIA, Univ. Nac. de Rosario, Rosario, ArgentinaComplementary 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 efficient 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 characterization 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 overlaps the original image. The Root-Mean-Square-Error (RMSE) between the estimated locations and the ones computed via a semiautomatic tool is calculated to evaluate the accuracy of the process. The method yields promising results.https://journal.info.unlp.edu.ar/JCST/article/view/743bioinformaticscdna microarraysimage analysisautomatic addressing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mónica G. Larese Juan Carlos Gómez |
spellingShingle |
Mónica G. Larese Juan Carlos Gómez Automatic Spot Adressing in cDNA Microarray Images Journal of Computer Science and Technology bioinformatics cdna microarrays image analysis automatic addressing |
author_facet |
Mónica G. Larese Juan Carlos Gómez |
author_sort |
Mónica G. Larese |
title |
Automatic Spot Adressing in cDNA Microarray Images |
title_short |
Automatic Spot Adressing in cDNA Microarray Images |
title_full |
Automatic Spot Adressing in cDNA Microarray Images |
title_fullStr |
Automatic Spot Adressing in cDNA Microarray Images |
title_full_unstemmed |
Automatic Spot Adressing in cDNA Microarray Images |
title_sort |
automatic spot adressing in cdna microarray images |
publisher |
Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata |
series |
Journal of Computer Science and Technology |
issn |
1666-6046 1666-6038 |
publishDate |
2008-07-01 |
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 efficient 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 characterization 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 overlaps the original image. The Root-Mean-Square-Error (RMSE) between the estimated locations and the ones computed via a semiautomatic tool is calculated to evaluate the accuracy of the process. The method yields promising results. |
topic |
bioinformatics cdna microarrays image analysis automatic addressing |
url |
https://journal.info.unlp.edu.ar/JCST/article/view/743 |
work_keys_str_mv |
AT monicaglarese automaticspotadressingincdnamicroarrayimages AT juancarlosgomez automaticspotadressingincdnamicroarrayimages |
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