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The increasing use of microarray technologies brought about a parallel demand in …


Home » Biology Articles » Bioinformatics » Functional profiling of microarray experiments using text-mining derived bioentities » Gene set enrichment analysis using bioentities

Gene set enrichment analysis using bioentities
- Functional profiling of microarray experiments using text-mining derived bioentities

 

Likewise, the way of studying the behavior of blocks of genes defined by bioentities is carried out by means of a segmentation test similar to the one used in FatiScan (Al-Shahrour et al., 2005). A pre-selection of genes is not necessary, only a ranked list is used in this test. Thus, given a list of genes arranged by any biological characteristic of the experiment (e.g. by differential expression between two types of experiments), a segmentation test is used to detect significant asymmetrical distributions of bioentities across it. Again, given the continuous nature of the bioentities, a Kolmogorov–Smirnov test is used to detect blocks of genes constitutively skewed to the extremes of the ranking and, consequently related to the biological criteria used for producing the ranking. This test is implemented in the MarmiteScan program and can be used in combination with the t-rex tool from the GEPAS (Montaner et al., 2006), which produces the ranked lists of genes for distinct microarray experimental designs.


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