01866nas a2200337   4500008004100000022001400041245010900055210006900164260001600233300001000249490000600259520081400265653001501079653002601094653001501120653002101135653001801156653002001174653001101194653001901205653001401224653002001238653001301258653002401271100001901295700003001314700001901344700002401363700002001387856012101407       2015                        eng d  a2045-232200aUsing activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity.0 aUsing activation status of signaling pathways as mechanismbased   c2015 Dec 18  a184940 v53 a<p>Many complex traits, as drug response, are associated with changes in biological pathways rather than being caused by single gene alterations. Here, a predictive framework is presented in which gene expression data are recoded into activity statuses of signal transduction circuits (sub-pathways within signaling pathways that connect receptor proteins to final effector proteins that trigger cell actions). Such activity values are used as features by a prediction algorithm which can efficiently predict a continuous variable such as the IC50 value. The main advantage of this prediction method is that the features selected by the predictor, the signaling circuits, are themselves rich-informative, mechanism-based biomarkers which provide insight into or drug molecular mechanisms of action (MoA). </p>10aAlgorithms10aAntineoplastic Agents10abiomarkers10aCell Line, Tumor10aCell Survival10agene expression10aHumans10aLethal Dose 5010aNeoplasms10aPhosphorylation10aProteins10aSignal Transduction1 aAmadoz, Alicia1 aSebastián-Leon, Patricia1 aVidal, Enrique1 aSalavert, Francisco1 aDopazo, Joaquin  uhttp://clinbioinfosspa.es/content/using-activation-status-signaling-pathways-mechanism-based-biomarkers-predict-drug02226nas a2200313   4500008004100000022001400041245008600055210006900141260001300210300001100223490000700234520127400241653001201515653001101527653001301538653000901551653002401560653002801584653002401612653001301636653001801649100003001667700002101697700002401718700002101742700002001763700002001783856010901803       2013                        eng d  a1362-496200aInferring the functional effect of gene expression changes in signaling pathways.0 aInferring the functional effect of gene expression changes in si  c2013 Jul  aW213-70 v413 a<p>Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case-control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/. </p>10aAnimals10aHumans10aInternet10aMice10aModels, Statistical10aReceptors, Cell Surface10aSignal Transduction10aSoftware10aTranscriptome1 aSebastián-Leon, Patricia1 aCarbonell, José1 aSalavert, Francisco1 aSánchez, Rubén1 aMedina, Ignacio1 aDopazo, Joaquin  uhttp://clinbioinfosspa.es/content/inferring-functional-effect-gene-expression-changes-signaling-pathways