After finishing my PhD in Computer Science and Artificial Intelligence at the University of Santiago de Compostela (Spain), I reoriented my research career to combine two of my passions: biomedicine and informatics. I started working as a postdoctoral researcher at the Food Toxicology Research Center of the French National Institute for Agricultural Research (INRAE) in Toulouse, in a project funded by the French National Cancer Institute (INCA). Here I was in charge of developing new computational methods to understand metabolic dysregulations in cancer due to mutations in the p53 gene and also in key target genes, combining previous biological knowledge with experimental data. During these years, I gained extensive knowledge on mathematical modeling for metabolism, as well as linear and  discrete optimization. One of the things I realized is that many challenges cannot be solved without knowledge of signaling and regulatory networks, and vice versa. Moreover, many of the methodological problems in metabolic modeling are also shared in causal modeling of regulatory networks. I joined the Saez-Rodríguez group at Heidelberg University as a Postdoctoral Researcher with the aim of improving some of the current technical and methodological issues of the current methods for causal inference of signalling networks, in the context of the European project PerMedCoE. This project aims to improve current methods and prepare them for pre-exascale computing, enabling large-scale modeling using omics data for personalized medicine.