Abstract
Many tasks in bioinformatics require the comprehensive evaluation of different types of data, generally available in distributed and heterogeneous data sources. Several approaches, including federated databases, multi databases and mediator based systems, have been proposed to integrate data from multiple sources. Yet, data warehousing seams to be the most adequate when numerous data need to be integrated, efficiently processed, and mined comprehensively. To support biological interpretation of high-throughput gene lists, we previously developed GFINDer (Genome Functional INtegrated Discoverer, http://www.bioinformatics.polimi.it/GFINDer/), a web server that statistically analyzes and mines functional and phenotypic gene annotations sparsely available in numerous databanks to highlight annotation categories significantly enriched or depleted in the considered gene lists. GFINDer includes a data warehouse that integrates gene and protein annotations of several organisms expressed through various controlled terminologies and ontologies. Here, we describe GFINDer data warehouse and discuss the lessons learned in its construction and five-year maintenance and development.
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Masseroli, M., Ceri, S., Campi, A. (2009). Integration and Mining of Genomic Annotations: Experiences and Perspectives in GFINDer Data Warehousing. In: Paton, N.W., Missier, P., Hedeler, C. (eds) Data Integration in the Life Sciences. DILS 2009. Lecture Notes in Computer Science(), vol 5647. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02879-3_8
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DOI: https://doi.org/10.1007/978-3-642-02879-3_8
Publisher Name: Springer, Berlin, Heidelberg
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