title: A call for virtual experiments: accelerating the scientific process.
abstract: Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. We argue that promoting the reuse of virtual experiments (the in silico analogues of wet-lab or field experiments) would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the translational application of models. A key step towards achieving this is that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. Lastly, we outline how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, transforming our approach to systems biology.
authors.affiliation: Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, UK. Electronic address: jonathan.cooper@cs.ox.ac.uk.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Cooper
authors.affiliation: Department of Animal and Aquacultural Sciences, Centre for Integrative Genetics, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway. Electronic address: jonovik@gmail.com.
authors.forename: Jon Olav
authors.initials: JO
authors.lastname: Vik
authors.affiliation: Department of Systems Biology and Bioinformatics, University of Rostock, D-18051 Rostock, Germany. Electronic address: dagmar.waltemath@uni-rostock.de.
authors.forename: Dagmar
authors.initials: D
authors.lastname: Waltemath
mesh_terms: D003198:Computer Simulation; D006801:Humans; D012106:Research; D012586:Science / Q000379:methods*
keywords: Computational physiology; Functional curation; Model comparison; Reproducible research; Virtual experiments