Model Sharing Working Group

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Model Sharing Working Group

Working Group leads: Peter Hunter; Herbert Sauro

Goals and Objectives:

The goals of this working group are to develop and promote: (i) modeling standards, (ii) software for authoring, visualisation and simulation of models, and (iii) model repositories that facilitate model reproducibility and model sharing. The group will provide an interface to international efforts on model sharing by the SBML consortium, the European VPH community, the IUPS Physiome community, the NeuroML project and the synthetic biology data exchange group.

Current Discussions

Discussion on Nature article: The case for open computer programs

Discussion on Automated Modular Construction of Models


Tuesday October 24, 2012 IMAG Meeting

Discussion topic: Progress in the last 12 months in the standards community

Please download the slides here

Wednesday October 19, 2011 4-5pm ET

Discussion topic: Model reproducibility and component/parts repositories

Please download slides here

Model Sharing Myths

1. Models are easily reproducible

This is common myth. One takes a model, enters it into a piece of software and the expectation is that one will get the same answer as published in the literature. Not necessarily true. Different tools implement numerical analysis methods differently, random number generators may have bias or different time steps or scale are used resulting in different simulation outcomes.

2. Extracting working models from the literature is trivial

This is a myth perpetrated by those who have never tried to extract a model from a published paper. Experience from the BioModels database project at EBI shows that at least 9 out of 10 of all models curated by EBI cannot be made to work from the published paper itself. This represents a huge waste of resources since models must be painstakingly recreated. One would assume this is especially true for multiscale models which are generally more complex than subcellular models. However no data is available on the creation of multiscale models from the literature.

Developing systematic methods to share models is one way to make the above myths come true. On the one hand standards such as SBML or CellML can be used to unambiguously describe a model but we have currently no way to unambiguously specify how to reproduce the results of simulating a model. It as if an experimentalists had no easy way to reproduce a published experiment.

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Peter Hunter - Auckland Bioengineering Institute (ABI), University of Auckland, New Zealand
Herbert Sauro - Bioengineering Dept, University of Washington, Seattle
Dan Beard - Bioengineering, Medical College Wisconsin (MCW)
Sharon Crook - Arizona State University
Ahmet Erdemir - Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic
Ion Moraru - University of Connecticut Health Center
Mark Musen - Stanford Center for Biomedical Informatics Research, Stanford University
Max Neal - Bioengineering, UW
Poul Nielsen - Auckland Bioengineering Institute (ABI), University of Auckland, New Zealand
James Schwaber - Thomas Jefferson University
Rajanikanth Vadigepalli - Thomas Jefferson University

Grace Peng (NIBIB)
Stephanie Sabourin (NIBIB)
German Cavelier (NIMH)
Peter Lyster (NIGMS)

Current State of the Art:

Model Databases
Biomodels Database,
BioModels Database
CellML Models

Markup Languages
SBGN (Systems Biology Graphical Notation)
SBML (Systems Biology Markup Language)
SEDML (Simulation Experiment Description Language)

Major Tools that Support Existing Standards

Antimony (CellML and SBML)
CellDesigner (SBML)
Copasi (SBML)
Core (CellML)
iBioSim (SBML)
JDesigner (SBML)
JSim (CellML and SBML)
OpenCell/PCEnv (CellML)
VCell (CellML and SBML)
cmgui (FieldML)
openCMISS (CellML, FieldML)

Challenges and Opportunities:

A specific challenge for this year is to have one or more of the IMAG groups using the existing modeling standards and to understand what the impediments are to wider use of standards by the IMAG community.

Journal Articles:

Overview of the SBML project

Huck M, Finney A, Sauro H. M. et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics. 19(4):524-531, 2003.

Overview of the IUPS Physiome project
Hunter, P.J. and Borg, T.K. Integration from proteins to organs: The Physiome Project. Nature Reviews Molecular and Cell Biology. 4:237-243, 2003.

Overview of the VPH project
Hunter, P., P.V. Coveney, B. de Bono, V. Diaz, J. Fenner, A.F. Frangi, P. Harris, R. Hose, P. Kohl, P. Lawford, K. McCormack, M. Mendes, S. Omholt, A. Quarteroni, J. Skar, J. Tegner, S. Randall Thomas, I. Tollis, I. Tsamardinos, J.H. van Beek, and M. Viceconti. A vision and strategy for the virtual physiological human in 2010 and beyond. Phil Trans A Math Phys Eng Sci. 368:2595-614, 2011.

Overview of the NeuroML project
Gleeson, P., S. Crook, R. Cannon, M. Hines, G. Billings, M. Farinella, T.M. Morse, A. Davison, S. Ray, U. Bhalla, S.R. Barnes, Y.D. Dmitrova, and R.A. Silver. NeuroML: a simulator-independent language for describing data-driven models of neurons and networks with a high degree of biological realism. PLoS Computational Biology. 6(6):e1000815, 2010.

Overview of the synthetic biology data exchange group

Past Presentations

Monday May 9, 2011 4-5pm ET

TITLE: The VPH/Physiome model repository
PRESENTERS: Tommy Yu, Randall Britten and Peter Hunter
Abstract: Models encoded in the CellML and FieldML formats are stored in a repository called PMR2 (Physiome Model Repository 2). This talk till explain the current features of the repository and its future development. We will also briefly discuss some of the open source software libraries that incorporate the application programming interfaces (APIs) to the model repository.

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