Abstract
Recent advances in DNA microarray technology have great impact on many areas of biomedical research and pharmacogenomics: discovering novel targets and genes, elucidating signatures of complex diseases, transcriptional profiling of models for diseases, and the development of individually optimized drugs based on differential gene expression patterns. Consequently, there is demand for robust methods for data analysis and the choice of adequate statistical tests. This review guides through all steps in the cDNA microarray data analysis pipeline and gives a basic understanding of the challenges in interpreting large microarray datasets.
Keywords: microarray, analysis, statistics, normalization, clustering
Current Topics in Medicinal Chemistry
Title: Analysis of DNA Microarray Data
Volume: 4 Issue: 13
Author(s): Hubert Hackl, Fatima Sanchez Cabo, Alexander Sturn, Olaf Wolkenhauer and Zlatko Trajanoski
Affiliation:
Keywords: microarray, analysis, statistics, normalization, clustering
Abstract: Recent advances in DNA microarray technology have great impact on many areas of biomedical research and pharmacogenomics: discovering novel targets and genes, elucidating signatures of complex diseases, transcriptional profiling of models for diseases, and the development of individually optimized drugs based on differential gene expression patterns. Consequently, there is demand for robust methods for data analysis and the choice of adequate statistical tests. This review guides through all steps in the cDNA microarray data analysis pipeline and gives a basic understanding of the challenges in interpreting large microarray datasets.
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Cite this article as:
Hackl Hubert, Cabo Sanchez Fatima, Sturn Alexander, Wolkenhauer Olaf and Trajanoski Zlatko, Analysis of DNA Microarray Data, Current Topics in Medicinal Chemistry 2004; 4 (13) . https://dx.doi.org/10.2174/1568026043387773
DOI https://dx.doi.org/10.2174/1568026043387773 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
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