title: Using argument notation to engineer biological simulations with increased confidence.
abstract: The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.
authors.affiliation: York Computational Immunology Laboratory, University of York, York, UK Centre for Immunology and Infection, University of York, York, UK Department of Electronics, University of York, York, UK kieran.alden@york.ac.uk.
authors.forename: Kieran
authors.initials: K
authors.lastname: Alden
authors.affiliation: York Computational Immunology Laboratory, University of York, York, UK Department of Computer Science, University of York, York, UK York Centre for Complex Systems Analysis, University of York, York, UK.
authors.forename: Paul S
authors.initials: PS
authors.lastname: Andrews
authors.affiliation: York Computational Immunology Laboratory, University of York, York, UK Department of Computer Science, University of York, York, UK York Centre for Complex Systems Analysis, University of York, York, UK.
authors.forename: Fiona A C
authors.initials: FA
authors.lastname: Polack
authors.affiliation: Faculdade de Medicina de Lisboa, Instituto de Medicina Molecular, Lisboa, Portugal.
authors.forename: Henrique
authors.initials: H
authors.lastname: Veiga-Fernandes
authors.affiliation: York Computational Immunology Laboratory, University of York, York, UK Centre for Immunology and Infection, University of York, York, UK SimOmics Ltd, The Catalyst, Baird Lane, Heslington, York, UK mark.coles@york.ac.uk.
authors.forename: Mark C
authors.initials: MC
authors.lastname: Coles
authors.affiliation: York Computational Immunology Laboratory, University of York, York, UK Department of Electronics, University of York, York, UK SimOmics Ltd, The Catalyst, Baird Lane, Heslington, York, UK jon.timmis@york.ac.uk.
authors.forename: Jon
authors.initials: J
authors.lastname: Timmis
mesh_terms: D000465:Algorithms; D000818:Animals; D002465:Cell Movement; D003198:Computer Simulation; D006801:Humans; D020407:Internet; D008221:Lymphoid Tissue / Q000473:pathology*; D008954:Models, Biological; D010581:Peyer's Patches / Q000502:physiology*; D012984:Software
keywords: Artoo; argumentation; computational modelling; immune system modelling; simulation