Using mathematical models to understand metabolism, genes, and disease

Abstract

Mathematical models are a useful tool for investigating a large number of questions in metabolism, genetics, and gene-environment interactions. A model based on the underlying biology and biochemistry is a platform for in silico biological experimentation that can reveal the causal chain of events that connect variation in one quantity to variation in another. We discuss how we construct such models, how we have used them to investigate homeostatic mechanisms, gene-environment interactions, and genotype-phenotype mapping, and how they can be used in precision and personalized medicine.