Microarray Probe Expression Measures, Data Normalization and Statistical Validation

DNA microarray technology is a high-throughput method for gaining information on gene function. Microarray technology is based on deposition/synthesis, in an ordered manner, on a solid surface, of thousands of EST sequences/genes/oligonucleotides. Due to the high number of generated datapoints, comp...

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Detalles Bibliográficos
Autores principales: Saviozzi, Silvia, Calogero, Raffaele A.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2003
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447370/
https://www.ncbi.nlm.nih.gov/pubmed/18629084
http://dx.doi.org/10.1002/cfg.312
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author Saviozzi, Silvia
Calogero, Raffaele A.
author_facet Saviozzi, Silvia
Calogero, Raffaele A.
author_sort Saviozzi, Silvia
collection PubMed
description DNA microarray technology is a high-throughput method for gaining information on gene function. Microarray technology is based on deposition/synthesis, in an ordered manner, on a solid surface, of thousands of EST sequences/genes/oligonucleotides. Due to the high number of generated datapoints, computational tools are essential in microarray data analysis and mining to grasp knowledge from experimental results. In this review, we will focus on some of the methodologies actually available to define gene expression intensity measures, microarray data normalization, and statistical validation of differential expression.
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spelling pubmed-24473702008-07-14 Microarray Probe Expression Measures, Data Normalization and Statistical Validation Saviozzi, Silvia Calogero, Raffaele A. Comp Funct Genomics Research Article DNA microarray technology is a high-throughput method for gaining information on gene function. Microarray technology is based on deposition/synthesis, in an ordered manner, on a solid surface, of thousands of EST sequences/genes/oligonucleotides. Due to the high number of generated datapoints, computational tools are essential in microarray data analysis and mining to grasp knowledge from experimental results. In this review, we will focus on some of the methodologies actually available to define gene expression intensity measures, microarray data normalization, and statistical validation of differential expression. Hindawi Publishing Corporation 2003-07 /pmc/articles/PMC2447370/ /pubmed/18629084 http://dx.doi.org/10.1002/cfg.312 Text en Copyright © 2003 Hindawi Publishing Corporation. http://creativecommons.org/licenses/by/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Saviozzi, Silvia
Calogero, Raffaele A.
Microarray Probe Expression Measures, Data Normalization and Statistical Validation
title Microarray Probe Expression Measures, Data Normalization and Statistical Validation
title_full Microarray Probe Expression Measures, Data Normalization and Statistical Validation
title_fullStr Microarray Probe Expression Measures, Data Normalization and Statistical Validation
title_full_unstemmed Microarray Probe Expression Measures, Data Normalization and Statistical Validation
title_short Microarray Probe Expression Measures, Data Normalization and Statistical Validation
title_sort microarray probe expression measures, data normalization and statistical validation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447370/
https://www.ncbi.nlm.nih.gov/pubmed/18629084
http://dx.doi.org/10.1002/cfg.312
work_keys_str_mv AT saviozzisilvia microarrayprobeexpressionmeasuresdatanormalizationandstatisticalvalidation
AT calogeroraffaelea microarrayprobeexpressionmeasuresdatanormalizationandstatisticalvalidation

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