Co-expressed Gene Groups Analysis (CGGA): An Automatic Tool for the Interpretation of Microarray Experiments

Ricardo Martinez 1 Nicolas Pasquier 1, * Claude Pasquier 2 Martine Collard 1 Lucero Lopez-Perez 3
* Auteur correspondant
1 I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis
2 IBV - Institut de Biologie Valrose
3 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
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
Keywords : Clustering Data Mining Genes and Functional Annotations Microarray Ontology Co-expression
Type de document :
Article dans une revue
Journal of Integrative Bioinformatics, Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2006, 3 (12), pp.1-12
Liste complète des métadonnées

Littérature citée [24 références]  Voir  Masquer  Télécharger
https://hal.archives-ouvertes.fr/hal-00172501
Contributeur : Claude Pasquier <>
Soumis le : lundi 26 avril 2010 - 09:18:01
Dernière modification le : vendredi 25 mai 2018 - 12:02:04
Document(s) archivé(s) le : mardi 14 septembre 2010 - 16:34:07

Fichier

Martinez_et_al._-_2006.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

  • HAL Id : hal-00172501, version 1

Collections

INRIA | UNICE | ENS-PARIS | I3S | PSL | UNIV-COTEDAZUR | ENPC | PARISTECH | INRIA-ROCQ

Citation

Ricardo Martinez, Nicolas Pasquier, Claude Pasquier, Martine Collard, Lucero Lopez-Perez. Co-expressed Gene Groups Analysis (CGGA): An Automatic Tool for the Interpretation of Microarray Experiments. Journal of Integrative Bioinformatics, Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2006, 3 (12), pp.1-12. 〈hal-00172501〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

540

Téléchargements de fichiers

176

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD