02621nas a2200325   4500008004100000022001400041245012100055210006900176260001600245300000900261490000700270520154400277653002101821653001901842653002901861653002001890653003401910653001301944653001101957653003201968100002402000700002002024700001902044700001902063700002402082700001902106700002002125700002002145856013002165       2012                        eng d  a1362-496200aDiscovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.0 aDiscovering the hidden subnetwork component in a ranked list of   c2012 Nov 01  ae1580 v403 a<p>Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein-protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network.</p>10aBipolar Disorder10aFanconi Anemia10aGene Regulatory Networks10aGenes, Neoplasm10aGenome-Wide Association Study10aGenomics10aHumans10aProtein Interaction Mapping1 aGarcía-Alonso, Luz1 aAlonso, Roberto1 aVidal, Enrique1 aAmadoz, Alicia1 aDe Maria, Alejandro1 aMinguez, Pablo1 aMedina, Ignacio1 aDopazo, Joaquin  uhttps://www.clinbioinfosspa.es/content/discovering-hidden-sub-network-component-ranked-list-genes-or-proteins-derived-genomic