01714nas a2200229   4500008004100000022001400041245009600055210006900151260001300220300001000233490000600243520095200249653003101201653002901232653001301261653002001274653001301294653002001307100001901327700002001346856011801366       2010                        eng d  a1744-838700aFunctional genomics and networks: new approaches in the extraction of complex gene modules.0 aFunctional genomics and networks new approaches in the extractio  c2010 Feb  a55-630 v73 a<p>The engine that makes the cell work is made of an intricate network of molecular interactions. Nowadays, the elements and relationships of this complex network can be studied with several types of high-throughput techniques. The dream of having a global picture of the cell from different perspectives that can jointly explain cell behavior is, at least technically, feasible. However, this task can only be accomplished by filling the gap between data and information. The availability of methods capable of accurately managing, integrating and analyzing the results from these experiments is crucial for this purpose. Here, we review the new challenges raised by the availability of different genomic data, as well as the new proposals presented to cope with the increasing data complexity. Special emphasis is given to approaches that explore the transcriptome trying to describe the modules of genes that account for the traits studied.</p>10aGene Expression Regulation10aGene Regulatory Networks10aGenomics10aProtein Binding10aProteins10aSystems biology1 aMinguez, Pablo1 aDopazo, Joaquin  uhttp://clinbioinfosspa.es/content/functional-genomics-and-networks-new-approaches-extraction-complex-gene-modules01718nas a2200277   4500008004100000022001400041245009000055210006900145260001600214300001100230490000700241520077800248653002801026653002301054653003001077653003801107653003201145653001301177653002001190653002401210100001901234700002501253700002001278700002001298856012201318       2007                        eng d  a1367-481100aFunctional profiling of microarray experiments using text-mining derived bioentities.0 aFunctional profiling of microarray experiments using textmining   c2007 Nov 15  a3098-90 v233 a<p><b>MOTIVATION: </b>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.</p>10aArtificial Intelligence10aDatabases, Protein10aGene Expression Profiling10aInformation Storage and Retrieval10aNatural Language Processing10aProteins10aResearch Design10aSystems Integration1 aMinguez, Pablo1 aAl-Shahrour, Fátima1 aMontaner, David1 aDopazo, Joaquin  uhttp://clinbioinfosspa.es/content/functional-profiling-microarray-experiments-using-text-mining-derived-bioentities-0