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Journal articles
Co-expressed Gene Groups Analysis (CGGA): An Automatic Tool for the Interpretation of Microarray Experiments
Abstract : Microarray technology produces vast amounts of data by measuring simultaneously the expression levels of thousands of genes under hundreds of biological conditions. Nowadays, one of the principal challenges in bioinformatics is the interpretation of this large amount of data using different sources of information. We have developed a novel data analysis method named CGGA (Co-expressed Gene Groups Analysis) that automatically finds groups of genes that are functionally enriched, i.e. have the same functional annotations, and are co-expressed. CGGA automatically integrates the information of microarrays, i.e. gene expression profiles, with the functional annotations of the genes obtained by the genome-wide information sources such as Gene Ontology. By applying CGGA to well-known microarray experiments, we have identified the principal functionally enriched and co-expressed gene groups, and we have shown that this approach enhances and accelerates the interpretation of DNA microarray experiments. CGGA program is available at http://www.i3s.unice.fr/~rmartine/CGGA
Cited literature [24 references]
https://hal.archives-ouvertes.fr/hal-00172501
Contributor : Claude Pasquier <>
Submitted on : Monday, April 26, 2010 - 9:18:01 AM
Last modification on : Tuesday, May 26, 2020 - 6:50:46 PM
Document(s) archivé(s) le : Tuesday, September 14, 2010 - 4:34:07 PM
Contributor : Claude Pasquier <>
Submitted on : Monday, April 26, 2010 - 9:18:01 AM
Last modification on : Tuesday, May 26, 2020 - 6:50:46 PM
Document(s) archivé(s) le : Tuesday, September 14, 2010 - 4:34:07 PM
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Martinez_et_al._-_2006.pdf
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