Combining biomedical knowledge and transcriptomic data to extract new knowledge on genes
Author(s) -
Guérin, Emilie,
Marquet, Gwenaëlle,
Chabalier, Julie,
Troadec, Marie-Bérengère,
Guguen-Guillouzo, Christiane,
Loréal, Olivier,
Burgun, Anita,
Moussouni, Fouzia
Publication year - 2007
Publication title -
pub – publications at bielefeld university (bielefeld university)
Language(s) - English
DOI - 10.2390/biecoll-jib-2006-35
Subject(s) - transcriptome , computational biology , gene , biology , computer science , human genome , genome , genetics , bioinformatics , genomics , identification (biology) , artificial intelligence
In biomedical research, interpretation of microarray data requires confrontation of data and knowledge from heterogeneous resources, either in the biomedical domain or in genomics, as well as restitution and analysis methods adapted to huge amounts of data. We present a combined approach that relies on two components: BioMeKE annotates sets of genes using biomedical GO and UMLS concepts, and GEDAW, a Gene Expression Data Warehouse, uses BioMeKE to enrich experimental results with biomedical concepts, thus performing complex analyses of expression measurements through analysis workflows. The strength of our approach has been demonstrated within the framework of analysis of data resulting from the liver transcriptome study. It allowed new genes potentially associated with liver diseases to be highlighted.
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