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MAGPIE: Simplifying access and execution of computational models in the life sciences.
Baldow, Christoph; Salentin, Sebastian; Schroeder, Michael; Roeder, Ingo; Glauche, Ingmar.
Affiliation
  • Baldow C; Institute for Medical Informatics and Biometry, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Salentin S; Biotechnology Center (BIOTEC), Technische Universität Dresden, Dresden, Germany.
  • Schroeder M; Biotechnology Center (BIOTEC), Technische Universität Dresden, Dresden, Germany.
  • Roeder I; Institute for Medical Informatics and Biometry, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Glauche I; National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
PLoS Comput Biol ; 13(12): e1005898, 2017 12.
Article in En | MEDLINE | ID: mdl-29244826
ABSTRACT
Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Biological Science Disciplines / Models, Biological Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: PLoS Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2017 Type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Biological Science Disciplines / Models, Biological Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: PLoS Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2017 Type: Article Affiliation country: Germany