@article {18789659,
	title = {Formulating and testing hypotheses in functional genomics},
	journal = {Artif Intell Med},
	volume = {45},
	number = {2-3},
	year = {2009},
	note = {<p>Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t Netherlands Artificial intelligence in medicine Artif Intell Med. 2009 Feb-Mar;45(2-3):97-107. Epub 2008 Sep 11.</p>},
	pages = {97-107},
	abstract = {<p>OBJECTIVE: The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the results, relating the available genomic information to the hypotheses that originated the experiment. METHODS AND RESULTS: Initially, this interpretation has been made on a pre-selection of relevant genes, based on the experimental values, followed by the study of the enrichment in some functional properties. Nevertheless, functional enrichment methods, demonstrated to have a flaw: the first step of gene selection was too stringent given that the cooperation among genes was ignored. The assumption that modules of genes related by relevant biological properties (functionality, co-regulation, chromosomal location, etc.) are the real actors of the cell biology lead to the development of new procedures, inspired in systems biology criteria, generically known as gene-set methods. These methods have been successfully used to analyze transcriptomic and large-scale genotyping experiments as well as to test other different genome-scale hypothesis in other fields such as phylogenomics.</p>},
	keywords = {babelomics, gene set analysis},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18789659},
	author = {Dopazo, J.}
}
