title: 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.
authors.affiliation: Department of Biology, Duke University, Durham, NC, 27708, USA. hfn@duke.edu.
authors.forename: H Frederik
authors.initials: HF
authors.lastname: Nijhout
authors.affiliation: Department of Mathematics, Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Janet A
authors.initials: JA
authors.lastname: Best
authors.affiliation: Department of Mathematics, Duke University, Durham, NC, 27708, USA.
authors.forename: Michael C
authors.initials: MC
authors.lastname: Reed
mesh_terms: D002874:Chromosome Mapping; D003198:Computer Simulation; D059647:Gene-Environment Interaction; D006706:Homeostasis; D006801:Humans; D008954:Models, Biological; D057285:Precision Medicine / Q000379:methods*