Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data.
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2021-05-15
Authors
Rian, Kinza
Hidalgo, Marta R
Çubuk, Cankut
Falco, Matias M
Loucera, Carlos
Esteban-Medina, Marina
Alamo-Alvarez, Inmaculada
Peña-Chilet, María
Dopazo, Joaquín
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Abstract
Genome-scale mechanistic models of pathways are gaining importance for genomic data interpretation because they provide a natural link between genotype measurements (transcriptomics or genomics data) and the phenotype of the cell (its functional behavior). Moreover, mechanistic models can be used to predict the potential effect of interventions, including drug inhibitions. Here, we present the implementation of a mechanistic model of cell signaling for the interpretation of transcriptomic data as an R/Bioconductor package, a Cytoscape plugin and a web tool with enhanced functionality which includes building interpretable predictors, estimation of the effect of perturbations and assessment of the effect of mutations in complex scenarios.
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Keywords
Causality, Mathematical modelling, Signaling pathway, Transcriptomic