Data Mining and Meta-Analysis on DNA Microarray Data

Data Mining and Meta-Analysis on DNA Microarray Data

Triantafyllos Paparountas, Maria Nefeli Nikolaidou-Katsaridou, Gabriella Rustici, Vasilis Aidinis
Copyright: © 2012 |Volume: 1 |Issue: 3 |Pages: 39
ISSN: 2160-9586|EISSN: 2160-9594|EISBN13: 9781466615151|DOI: 10.4018/ijsbbt.2012070101
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MLA

Paparountas, Triantafyllos, et al. "Data Mining and Meta-Analysis on DNA Microarray Data." IJSBBT vol.1, no.3 2012: pp.1-39. http://doi.org/10.4018/ijsbbt.2012070101

APA

Paparountas, T., Nikolaidou-Katsaridou, M. N., Rustici, G., & Aidinis, V. (2012). Data Mining and Meta-Analysis on DNA Microarray Data. International Journal of Systems Biology and Biomedical Technologies (IJSBBT), 1(3), 1-39. http://doi.org/10.4018/ijsbbt.2012070101

Chicago

Paparountas, Triantafyllos, et al. "Data Mining and Meta-Analysis on DNA Microarray Data," International Journal of Systems Biology and Biomedical Technologies (IJSBBT) 1, no.3: 1-39. http://doi.org/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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