Path2Models: large-scale generation of computational models from biochemical pathway maps
- Equal contributors
1 European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
2 Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen 72076, Germany
3 Babraham Institute, Babraham Research Campus, Cambridge, UK
4 Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, UK
5 Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben D-06466, Germany
6 HITS gGmbH, D-69118, Heidelberg, Germany
7 Caulfield School of Information Technology, Monash University, Victoria 3800, Australia
8 Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125, USA
9 School of Chemistry, The University of Manchester, Manchester M13 9PL, UK
10 School of Computer Science, The University of Manchester, Manchester M13 9PL, UK
11 Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA
12 Instituto Gulbenkian de Ciência (IGC), Oeiras P-2780-156, Portugal
13 Institute of Computer Science, University of Halle-Wittenberg, Halle, Germany
14 Present address: University of California, San Diego, Bioengineering Department, La Jolla, CA 92093-0412, USA
BMC Systems Biology 2013, 7:116 doi:10.1186/1752-0509-7-116Published: 1 November 2013
Systems biology projects and omics technologies have led to a growing number of biochemical pathway models and reconstructions. However, the majority of these models are still created de novo, based on literature mining and the manual processing of pathway data.
To increase the efficiency of model creation, the Path2Models project has automatically generated mathematical models from pathway representations using a suite of freely available software. Data sources include KEGG, BioCarta, MetaCyc and SABIO-RK. Depending on the source data, three types of models are provided: kinetic, logical and constraint-based. Models from over 2 600 organisms are encoded consistently in SBML, and are made freely available through BioModels Database at http://www.ebi.ac.uk/biomodels-main/path2models webcite. Each model contains the list of participants, their interactions, the relevant mathematical constructs, and initial parameter values. Most models are also available as easy-to-understand graphical SBGN maps.
To date, the project has resulted in more than 140 000 freely available models. Such a resource can tremendously accelerate the development of mathematical models by providing initial starting models for simulation and analysis, which can be subsequently curated and further parameterized.