19 1 General Introduction Systems medicine approach and computational models Systems medicine is the multidisciplinary combination of different fields including biology, informatics, computational modeling and mathematics to gap the bridge between new translational research and traditional health care123. This interdisciplinary methodology allows clinical investigators and physicians to team up with mathematicians and natural scientists, to tackle different medical problems in a more efficient and tailored manner124. Their approaches commonly rely on in vitro and in vivo systems, combined with various ‘omics technologies as well as different computational approaches (in silico systems). Computational models are in silico representations of biological systems that can help us understand regulation of different biological processes. These models mathematically describe a biological system in an integrative way. Simulating their response to interventions or mutations can help us predict behaviors and outcomes of a given system under different conditions. In this thesis I will focus on computational models of metabolic pathways. One main type of metabolic computational models is a detailed kinetic model. Kinetic models for the study of metabolic pathways are based on kinetic equations describing the behavior of the enzymes of a given pathway combined with kinetic parameters commonly obtained from the literature or measured in the lab. Ordinary differential equations (ODEs) are then used to describe the dynamics of reactions in the system and how these produce and consume different metabolites. These dynamic models can predict both metabolite concentrations and fluxes over time. An interesting aspect of detailed kinetic models is the possibility to study Metabolic Control Analysis to understand the control that certain enzymes exert over metabolite concentrations or metabolic fluxes in a specific pathway125,126. In order to adapt computational models to different conditions, such as different tissues or diseases, enzyme concentrations can be measured and introduced into the model. To do so, proteomics data or enzyme activity data are commonly used. There are models describing different metabolic pathways such as mitochondrial β-oxidation95, TCA and ECT127 and glucose metabolism128. So far, to the best of my knowledge, no computational models describing peroxisomal β-oxidation have been published. Another highly valuable type of computational model for the study of systems medicine is based on deep learning (DL) algorithms. These models are often referred to as ‘multilayered’ due to their ability to process data in different layers in which they transform the data and pass them on to the next layer until
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