Çubut, CankutHidalgo, Marta R.Amadoz, AliciaRian, KinzaSalavert, FranciscoPujana, Miguel AngelMateo, FrancescaHerranz Ors, Carmen, 1992-Carbonell-Caballero, JoseDopazo, Joaquín2020-04-072020-04-072019Çubuk C, Hidalgo MR, Amadoz A, Rian K, Salavert F, Pujana MA, Mateo F, Herranz C, Carbonell-Caballero J, Dopazo J. Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models. NPJ Syst Biol Appl. 2019; 5:7. DOI: 10.1038/s41540-019-0087-22056-7189http://hdl.handle.net/10230/44175In spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. We present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway metabolic module activities that can also be used for class prediction and in silico prediction of knock-out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. Metabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.application/pdfeng© The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s41540-019-0087-2CancerMetabolic engineeringSoftwareinfo:eu-repo/semantics/openAccess