A Data Warehousing Approach for Genomics Data Meta-Analysis

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Author(s): Martine Collard (INRIA Sophia Antipolis and University of Nice-Sophia Antipolis, France), Leila Kefi-Khelif (INRIA Sophia Antipolis, France), Van Trang Tran (I3S laboratory and University of Nice-Sophia Antipolis, France)and Olivier Corby (INRIA Sophia Antipolis, France)
Copyright: 2010
Pages: 33
Source title: Evolving Application Domains of Data Warehousing and Mining: Trends and Solutions
Source Author(s)/Editor(s): Pedro Nuno San-Banto Furtado (University of Coimbra, Portugal)
DOI: 10.4018/978-1-60566-816-1.ch007

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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Abstract

DNA micro-array is a fastest-growing technology in molecular biology and bioinformatics. Based on series of microscopic spots of DNA sequences, they allow the measurement of gene expression in specific conditions at a whole genome scale. Micro-array experiments result in wide sets of expression data that are useful to the biologist to investigate various biological questions. Experimental micro-arrays data and sources of biological knowledge are now available on public repositories. As a consequence, comparative analyses involving several experiments become conceivable and hold potentially relevant knowledge. Nevertheless, the task of manually navigating and searching for similar tendencies in such huge spaces is mainly impracticable for the investigator and leads to limited results. In this context, the authors propose a semantic data warehousing solution based on semantic web technologies that allows to monitoring both the diversity and the volume of all related data.

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A Data Warehousing Approach for Genomics Data Meta-Analysis

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