01569nas a2200229   4500008004100000022001400041245003200055210003100087260000900118300001100127490000800138520093500146653001201081653002601093653002001119653003001139653001101169653004401180100002001224700002501244856007001269       2008                        eng d  a1064-374500aExpression and microarrays.0 aExpression and microarrays  c2008  a245-550 v4533 a<p>High throughput methodologies have increased by several orders of magnitude the amount of experimental microarray data available. Nevertheless, translating these data into useful biological knowledge remains a challenge. There is a risk of perceiving these methodologies as mere factories that produce never-ending quantities of data if a proper biological interpretation is not provided. Methods of interpreting these data are continuously evolving. Typically, a simple two-step approach has been used, in which genes of interest are first selected based on thresholds for the experimental values, and then enrichment in biologically relevant terms in the annotations of these genes is analyzed in a second step. For various reasons, such methods are quite poor in terms of performance and new procedures inspired by systems biology that directly address sets of functionally related genes are currently under development.</p>10aAnimals10aComputational Biology10agene expression10aGene Expression Profiling10aHumans10aOligonucleotide Array Sequence Analysis1 aDopazo, Joaquin1 aAl-Shahrour, Fátima  uhttps://www.clinbioinfosspa.es/content/expression-and-microarrays