@article{Chabalier2007,
abstract = {Interpretation of transcriptomic data is usually made through a "standard" approach which consists in clustering the genes according to their expression patterns and exploiting Gene Ontology (GO) annotations within each expression cluster. This approach makes it difficult to underline functional relationships between gene products that belong to different expression clusters. To address this issue, we propose a transversal analysis that aims to predict functional networks based on a combination of GO processes and data expression.},
author = {Chabalier, Julie and Mosser, Jean and Burgun, Anita},
doi = {10.1186/1471-2105-8-235},
issn = {1471-2105},
journal = {BMC Bioinformatics},
keywords = {Caco-2 Cells,Cell Differentiation,Cell Line,Cluster Analysis,Controlled,Data Interpretation,Databases,Enterocytes,Enterocytes: physiology,Gene Expression Profiling,Gene Expression Profiling: methods,Gene Expression Regulation,Gene Regulatory Networks,Humans,Natural Language Processing,Neoplastic,Neoplastic: genetics,Oligonucleotide Array Sequence Analysis,Oligonucleotide Array Sequence Analysis: methods,Protein,Protein Interaction Mapping,Proteins,Proteins: classification,Proteins: physiology,SML-LIB-BIBLIO,Statistical,Tumor,User-Computer Interface,Vocabulary,lang:ENG},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
month = jan,
pages = {235},
pmid = {17605807},
title = {{A transversal approach to predict gene product networks from ontology-based similarity.}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1940024\&tool=pmcentrez\&rendertype=abstract},
volume = {8},
year = {2007}
}