Title: EuroDia: a beta-cell gene expression resource
Authors: Liechti, Robin ×
Csárdi, Gábor
Bergmann, Sven
Schütz, Frédéric
Sengstag, Thierry
Boj, Sylvia F
Servitja, Joan-Marc
Ferrer, Jorge
Van Lommel, Leentje
Schuit, Frans
Klinger, Sonia
Thorens, Bernard
Naamane, Najib
Eizirik, Decio L
Marselli, Lorella
Bugliani, Marco
Marchetti, Piero
Lucas, Stephanie
Holm, Cecilia
Jongeneel, C Victor
Xenarios, Ioannis #
Issue Date: 2010
Series Title: Database-The Journal of Biological Databases and Curation
Article number: baq024
Abstract: Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL:
ISSN: 1758-0463
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Gene Expression Unit
× corresponding author
# (joint) last author

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