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Microarray Data Analysis and Mining Tools

Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxic...

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Detalles Bibliográficos
Autores principales: Selvaraj, Saravanakumar, Natarajan, Jeyakumar
Formato: Texto
Lenguaje:English
Publicado: Biomedical Informatics 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3089881/
https://www.ncbi.nlm.nih.gov/pubmed/21584183
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author Selvaraj, Saravanakumar
Natarajan, Jeyakumar
author_facet Selvaraj, Saravanakumar
Natarajan, Jeyakumar
author_sort Selvaraj, Saravanakumar
collection PubMed
description Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis.
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spelling pubmed-30898812011-05-16 Microarray Data Analysis and Mining Tools Selvaraj, Saravanakumar Natarajan, Jeyakumar Bioinformation Hypothesis Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis. Biomedical Informatics 2011-04-22 /pmc/articles/PMC3089881/ /pubmed/21584183 Text en © 2011 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Hypothesis
Selvaraj, Saravanakumar
Natarajan, Jeyakumar
Microarray Data Analysis and Mining Tools
title Microarray Data Analysis and Mining Tools
title_full Microarray Data Analysis and Mining Tools
title_fullStr Microarray Data Analysis and Mining Tools
title_full_unstemmed Microarray Data Analysis and Mining Tools
title_short Microarray Data Analysis and Mining Tools
title_sort microarray data analysis and mining tools
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3089881/
https://www.ncbi.nlm.nih.gov/pubmed/21584183
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