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Data Mining and Meta-Analysis on DNA Microarray Data
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Author(s): Triantafyllos Paparountas (Biomedical Sciences Research Center “Alexander Fleming”, Greece), Maria Nefeli Nikolaidou-Katsaridou (Biomedical Sciences Research Center “Alexander Fleming”, Greece), Gabriella Rustici (European Molecular Biology Laboratory-European Bioinformatics Institute, UK)and Vasilis Aidinis (Biomedical Sciences Research Center “Alexander Fleming”, Greece)
Copyright: 2012
Volume: 1
Issue: 3
Pages: 39
Source title:
International Journal of Systems Biology and Biomedical Technologies (IJSBBT)
Editor(s)-in-Chief: Tagelsir Mohamed Gasmelseid (International University of Africa, Sudan)
DOI: 10.4018/ijsbbt.2012070101
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Abstract
Microarray technology enables high-throughput parallel gene expression analysis, and use has grown exponentially thanks to the development of a variety of applications for expression, genetics and epigenetic studies. A wealth of data is now available from public repositories, providing unprecedented opportunities for meta-analysis approaches, which could generate new biological information, unrelated to the original scope of individual studies. This study provides a guideline for identification of biological significance of the statistically-selected differentially-expressed genes derived from gene expression arrays as well as to suggest further analysis pathways. The authors review the prerequisites for data-mining and meta-analysis, summarize the conceptual methods to derive biological information from microarray data and suggest software for each category of data mining or meta-analysis.
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