Common ground between modelers and simulation software:The Systems Biology Markup Language (SBML)

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MIRIAM

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Mike Hucka California Institute of Technology, Pasadena, CA, US

Frank Bergmann California Institute of Technology, Pasadena, CA, US

Sarah Keating European Bioinformatics Institute, Cambridge, UK

Chris Myers University of Utah, Salt Lake City, UT, US

James Schaff U. Connecticut Health Center, Farmington, CT, US

Lucian Smith University of Washington, Seattle, WA, US

Mike Hucka California Institute of Technology, Pasadena, CA, US

Sarah Keating European Bioinformatics Institute, Cambridge, UK

Lucian Smith University of Washington, Seattle, WA, US

Linda Taddeo California Institute of Technology, Pasadena, CA, US

• Species: pools of entities of the same kind located in a compartment and participating in reactions (processes).

The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biological processes. It's applicable to simulations of metabolism, cell-signaling, and many other topics.

Example components of an SBML model:

SBML Level 3 Core released 6 October 2010See http://sbml.org/Documents/Specifications

Support for SBML infrastructure and software development provided by NIGMS grant GM070923.

Frank Bergmann California Institute of Technology, Pasadena, CA, US

SBO

SED-ML

• Compartments: well-stirred containers of finite size where species are located.

• Reactions: statements describing transformation, transport or binding processes that change the amount of one or more species.

• Parameters: quantities with symbolic names, usable in mathematical formulas throughout a model.

• Events: statements describing discontinuous, instantaneous changes in the values of one or more variables of any type (e.g., species).

SBML Level 3 defines a mechanism whereby packages can add syntax and semantics for new features. Examples being developed today:

• Multicellular/multicomponent species: species with internal state, structure & bonds between individual entities.

• Qualitative models: formalisms such as Boolean networks and Petri Nets.

• Flux balance constraints: steady-state models (e.g., for flux-balance analysis).

• Spatial models: models where compartments are spatially inhomogeneous and processes involve spatial variables.

The Systems Biology Ontology (SBO) provides a set of controlled vocabulariesthat can be used to make the mathematical meaning of a model more precise and machine-readable. Each component of model can be annotated with references to terms from SBO, allowing software to “understand” what kind of entities they are. The result: software can work more intelligently with models.

Today, various software systems use SBO terms to give users impressive new capabilities for working with SBML models.

Find out more about SBO at http://biomodels.net/sbo

The guidelines for the Minimum Information Requested in the Annotationof biochemical Models (MIRIAM) define a simple approach for two importantaspects of reusable models:

• The minimum information a model should contain in order for readers to be able to trace its provenance, and

• A simple scheme for encoding both the provenance data as well as references to external data sources (such as external databases).

Find out more about MIRIAM at http://biomodels.net/miriam

Reproducing the results of using a model requires having more than justthe model at hand: it requires knowing such things as the simulation systemused, the software settings, the initial and starting conditions for the modelexecution, the way that the output data was arranged, and so on.

The Simulation Experiment Description Markup Language (SED-ML) is asoftware-independent format for recording such data in a way that can beused and exchanged by many different software systems. Its aim is to answer the question “How was this model used to produce that result?”

Find out more about SED-ML at http://sed-ml.org

Over 230 software systems support SBML today.See http://sbml.org/SBML_Software_Guide

SBML Level 3