PP132. MINING GENE EXPRESSION DATA FROM MULTIPLE MICROARRAY STUDIES USING GENE ONTOLOGY ANNOTATION: APPLICATION TO NEURODEGENERATIVE DISORDERS
ANDREJ KASTRIN, Borut Peterlin Division of Medical Genetics, Department of Obstetrics and Gynecology, University Medical Centre, SI-1000 Ljubljana, Slovenia e-mail: andrej.kastrin@guest.arnes.si
*Corresponding Author:
page: 107

Abstract

Application of microarray technology is rapidly producing enormous amounts of data that necessitate new approaches of data analysis. Performing systematic review strategies for combining results from microarray experiments is the first cruical step in the process of knowledge discovery. The aim of this study was the comparison of gene expression profiles using Gene Ontology (GO) constraint in the domain of neurodegenerative disorders. Interstudy analysis were carried out on 1490 human genes that have been reported as differentially expressed in a subset of 20 full-text articles retrieved by PubMed. Our results indicated that UniGene-based matching reveals moderate relationship of gene expression between experiments. We next employed GO annotation system to group genes into functional categories. R efined matching based on semantic links between the entries of GO vocabulary significantly improves the quality of matches. Beyond the specific implications for neurodegenerative disorders, this work establishes a possible framework for the evaluation, cross-validation, and comparison of publicly availably gene expression data.




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