O papel modulador do gene AIRE - capes

Analysis of Microarray (SAM) [10], which is based on t test statistics specificallydeveloped for high-throughput microarray data.Although these methods are useful tools for the identification of differentiallyexpressed genes, they not permit the determination of interactions betweengenes.There are several computational solutions proposed in the literature to infergene networks; the approaches based on the mathematical formalism of theinformation theory as ARACNE proram [29,30], the algorithms that considerordinary differential equations as NIR, NMI and TSNI programs [31-33] andthose which solve the inference problem by means of Bayesian networks asBanjo [34] and GeneNetwork [12] programs.Comparing the algorithms, GeneNetwork was chosen for the analysispurposes due to its differential features. The algorithm realizes the interpolationof data and is able to handle with more than one thousand of genes. Moreover,the resulting network is described by an oriented graph in which positive arrowsindicate induction and negative ones denote repression between genes.In an effort to provide a clearer understanding of the high-throughput dataresulting from microarray experiments and to establish regulatory geneinteractions during murine thymus ontogeny, normalized data were analyzed bythe GeneNetwork program [12], which is based on dynamic Bayesian statisticsinferring gene networks.Recently, gene networks were reconstructed based on microarray datastudying model organisms, such as S. cerevisiae [35], E. coli [36] andDrosophila [37]. Additionally, gene networks were reconstructed for mammalian246