|Title||Functional profiling of microarray experiments using text-mining derived bioentities|
|Publication Type||Journal Article|
|Year of Publication||2007|
|Authors||Minguez, P, Al-Shahrour, F, Montaner, D, Dopazo, J|
|Keywords||Artificial Intelligence *Databases; babelomics; Protein Gene Expression Profiling/*methods Information Storage and Retrieval/*methods *Natural Language Processing Proteins/*classification/*metabolism Research/*methods Systems Integration|
MOTIVATION: The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.
Minguez, Pablo Al-Shahrour, Fatima Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov’t England Bioinformatics (Oxford, England) Bioinformatics. 2007 Nov 15;23(22):3098-9. Epub 2007 Sep 13.