title: The inverse problem in mathematical biology.
abstract: Biological systems present particular challengers to model for the purposes of formulating predictions of generating biological insight. These systems are typically multi-scale, complex, and empirical observations are often sparse and subject to variability and uncertainty. This manuscript will review some of these specific challenges and introduce current methods used by modelers to construct meaningful solutions, in the context of preserving biological relevance. Opportunities to expand these methods are also discussed.
authors.affiliation: Crisma Center, Departments of Critical Care Medicine, Mathematics, and Chemical Engineering, University of Pittsburgh, 200 Lothrop St, Pittsburgh, PA 16123, USA. Electronic address: clermontg@upmc.edu.
authors.forename: Gilles
authors.initials: G
authors.lastname: Clermont
authors.affiliation: Department of Anesthesiology and Intensive Care Medicine, University of Bonn Medical Center, Sigmund-Freud-Str. 25, Bonn, 53105, Germany. Electronic address: cler@pitt.edu.
authors.forename: Sven
authors.initials: S
authors.lastname: Zenker
mesh_terms: D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical
keywords: Biological systems; Ensemble models; Inverse problem; Parameter estimation