Advances in Astrocyte Computational Models: From Metabolic Reconstructions to Multi-omic Approaches - González, Janneth; Pinzón, Andrés; Angarita-Rodríguez, Andrea; Aristizabal, Andrés Felipe; Barreto, George E.; Martín-Jiménez, Cynthia (Frontiers in Neuroinformatics, 2020)
The growing importance of astrocytes in the field of neuroscience has led to a greater number of computational models devoted to the study of astrocytic functions and their metabolic interactions with neurons. The modeling of these interactions demands a combined understanding of brain physiology and the development of computational frameworks based on genomic-scale reconstructions, system biology, and dynamic models. These computational approaches have helped to highlight the neuroprotective mechanisms triggered by astrocytes and other glial cells, both under normal conditions and during neurodegenerative processes. In the present review, we evaluate some of the most relevant models of astrocyte metabolism, including genome-scale reconstructions and astrocyte-neuron interactions developed in the last few years. Additionally, we discuss novel strategies from the multi-omics perspective and computational models of other glial cell types that will increase our knowledge in brain metabolism and its association with neurodegenerative diseases.