Large-scale generation of computational models from biochemical pathway maps

التفاصيل البيبلوغرافية
العنوان: Large-scale generation of computational models from biochemical pathway maps
المؤلفون: Büchel, Finja, Rodriguez, Nicolas, Swainston, Neil, Wrzodek, Clemens, Czauderna, Tobias, Keller, Roland, Mittag, Florian, Schubert, Michael, Glont, Mihai, Golebiewski, Martin, van Iersel, Martijn, Keating, Sarah, Rall, Matthias, Wybrow, Michael, Hermjakob, Henning, Hucka, Michael, Kell, Douglas B., Müller, Wolfgang, Mendes, Pedro, Zell, Andreas, Chaouiya, Claudine, Saez-Rodriguez, Julio, Schreiber, Falk, Laibe, Camille, Dräger, Andreas, Novère, Nicolas Le
المصدر: BMC Systems Biology 2013, 7:116
سنة النشر: 2013
المجموعة: Quantitative Biology
مصطلحات موضوعية: Quantitative Biology - Molecular Networks
الوصف: Background: Systems biology projects and omics technologies have led to a growing number of biochemical pathway reconstructions. However, mathematical models are still most often created de novo, based on reading the literature and processing pathway data manually. Results: To increase the efficiency with which such models can be created, we automatically generated mathematical models from pathway representations using a suite of freely available software. We produced models that combine data from KEGG PATHWAY, BioCarta, MetaCyc and SABIO-RK; According to the source data, three types of models are provided: kinetic, logical and constraint-based. All models are encoded using SBML Core and Qual packages, and available through BioModels Database. Each model contains the list of participants, the interactions, and the relevant mathematical constructs, but, in most cases, no meaningful parameter values. Most models are also available as easy to understand graphical SBGN maps. Conclusions: to date, the project has resulted in more than 140000 models freely available. We believe this resource can tremendously accelerate the development of mathematical models by providing initial starting points ready for parametrization.
Comment: 29 pages, 8 figures
نوع الوثيقة: Working Paper
DOI: 10.1186/1752-0509-7-116
URL الوصول: http://arxiv.org/abs/1307.7005
رقم الأكسشن: edsarx.1307.7005
قاعدة البيانات: arXiv