Arnau Montagud , Miguel Ponce-de-Leon , Alfonso Valencia
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Systems biology at the giga-scale: Large multiscale models of complex, heterogeneous multicellular systems
Agent-based modelling has proven its usefulness in several biomedical projects by explaining and uncovering mechanisms in diseases. Nevertheless, the scenarios addressed in these models usually consider a small number of cells, lack cell-specific characterisation and dynamic interactions and have a simplistic environment description. Tools that enable scalable, real-sized simulations of biological systems that require complex setups are needed to have simulations closer to biomedical scenarios that can capture cell-to-cell heterogeneity and system-wide emerging properties. To deliver simulations at the giga-scale (109 cells), different tools have implemented technologies to run in high-performance computing clusters. We hereby review these efforts and detail the main areas of improvement the field needs to focus on to have simulations that are a step closer to having digital twins.
期刊介绍:
Current Opinion in Systems Biology is a new systematic review journal that aims to provide specialists with a unique and educational platform to keep up-to-date with the expanding volume of information published in the field of Systems Biology. It publishes polished, concise and timely systematic reviews and opinion articles. In addition to describing recent trends, the authors are encouraged to give their subjective opinion on the topics discussed. As this is such a broad discipline, we have determined themed sections each of which is reviewed once a year. The following areas will be covered by Current Opinion in Systems Biology: -Genomics and Epigenomics -Gene Regulation -Metabolic Networks -Cancer and Systemic Diseases -Mathematical Modelling -Big Data Acquisition and Analysis -Systems Pharmacology and Physiology -Synthetic Biology -Stem Cells, Development, and Differentiation -Systems Biology of Mold Organisms -Systems Immunology and Host-Pathogen Interaction -Systems Ecology and Evolution