Path2Models project page

Path2Models is a collection of models automatically generated from pathway resources such as KEGG, BioCarta, MetaCyc, PID and SABIO-RK and hosted in BioModels database.

The approximately 140,000 models in the Path2Models project are now grouped taxonomically into 812 bundles, typically one per genus. Each such bundle contains one representative entry, typically a genome scale model for one of the organisms under that genus. The description of a representative SBML model contains the BioModels accessions of all models under this bundle along with metadata information. The other models of the group are available as a COMBINE archive alongside the main file. All requests to access a model inside a COMBINE archive will be redirected to the representative model.

Browsing models

The models can be accessed through the dedicated browse page. We currently only offer textual search capabilities for these models. We are working hard to consolidate this in the near future. Thank you for your patience and undestanding during this time.

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Additional information

These automatically generated models are only partially parameterised. In the case of KEGG signaling pathways for which no mechanistic details are provided, the models (with qual constructs) contain only topological relationships together with interaction signs. No logical rules specify the effects of (combined) interactions, and these models should be seen as scaffolds to be further parameterised before use in simulation. This can be done either by considering default, yet biologically meaningful, logical functions (e.g., requiring the presence of at least one activator and absence of all inhibitors) [Nobeli2003], by doing further manual refinement of the model (e.g., by literature mining), or by using dedicated experimental data to identify the functions [MacNamara2012].

Several simulation tools now support the SBML Level 3 qual package, including GINsim, CellNOpt and The Cell Collective platform. CellNOpt provides a pipeline to generate logical rules by pruning a general scaffold with all possible rules so as to find the submodel that best describes the data. This can be done using various formalisms [Terfve2012] of increasing detail, depending of the data at hand. The Cell Collective platform includes Bio-Logic Builder to facilitate the conversion of biological knowledge into a computational model [Helikar2012]. GINsim provides complementary features that allow performing multiple analyses of logical models using powerful algorithms [Chaouiya2012]. Therefore, relying on a combined use of these tools, one could use the Path2Models qualitative models by training them against data of, for instance, a cell type of interest, and subsequently analysing the resulting models.


For more information about the initial effort behind this branch, please refer to the Github project page of path2models. This project has now been completed. Models generated from other efforts are added to this branch.

If you use models generated by the Path2Models project, please cite:

Finja Büchel, Nicolas Rodriguez, Neil Swainston, Clemens Wrzodek, Tobias Czauderna, Roland Keller, Florian Mittag, Michael Schubert, Mihai Glont, Martin Golebiewski, Martijn van Iersel, Sarah Keating, Matthias Rall, Michael Wybrow, Henning Hermjakob, Michael Hucka, Douglas B Kell, Wolfgang Müller, Pedro Mendes, Andreas Zell, Claudine Chaouiya, Julio Saez-Rodriguez, Falk Schreiber, Laibe, Camille, Andreas Dräger and Nicolas Le Novère
Path2Models: large-scale generation of computational models from biochemical pathway maps.
BMC Systems Biology 2013, 7:116
[Access to this publication]

If you use models generated from the Pathway Interaction Database, please cite:

Finja Büchel, Clemens Wrzodek, Florian Mittag, Andreas Dräger, Johannes Eichner, Nicolas Rodriguez, Nicolas Le Novère, and Andreas Zell
Qualitative translation of relations from BioPAX to SBML qual.
Bioinformatics 2012, 28(20):2648-2653
[Access to this publication]

For general BioModels Database reference information, please see our citation page.