Large-scale generation of computational models from biochemical pathway maps
Abstract
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.
Cite
@article{arxiv.1307.7005,
title = {Large-scale generation of computational models from biochemical pathway maps},
author = {Finja Büchel and Nicolas Rodriguez and Neil Swainston and Clemens Wrzodek and Tobias Czauderna and Roland Keller and Florian Mittag and Michael Schubert and Mihai Glont and Martin Golebiewski and Martijn van Iersel and Sarah Keating and Matthias Rall and Michael Wybrow and Henning Hermjakob and Michael Hucka and Douglas B. Kell and Wolfgang Müller and Pedro Mendes and Andreas Zell and Claudine Chaouiya and Julio Saez-Rodriguez and Falk Schreiber and Camille Laibe and Andreas Dräger and Nicolas Le Novère},
journal= {arXiv preprint arXiv:1307.7005},
year = {2013}
}
Comments
29 pages, 8 figures