A Data Warehousing Approach for Genomics Data Meta-Analysis - Evolving Application Domains of Data Warehousing and Mining - page 129

Chapter 7
A Data Warehousing
Approach for Genomics
Data Meta-Analysis

Martine Collard
INRIA Sophia Antipolis, France and University of Nice-Sophia Antipolis, France

Leila Kefi-Khelif
INRIA Sophia Antipolis, France

Van Trang Tran
I3S laboratory, University of Nice-Sophia Antipolis, France

Olivier Corby
INRIA Sophia Antipolis, France

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.

IntroductIon variety of biological issues. Numerous laboratories

have collected micro-array data that are available
on public databases and web sites. For instance, the
Gene Express Omnibus 1 (GEO) or theArrayExpress 2
repositories provide public availability of data on

DNA micro-arrays are now widely used for mRNA
expression profiling and have applications in a