Systems Biology Markup Language

Ranjit Randhawa

Department of Computer Science

Virginia Tech

Outline

• Background• Motivation and Introduction

– Language details

• SBML Overview– Components– Parsers

• Sample Model• Future of SBML• Comments and Questions

Background

• Systems biology – “synergistic integration of theory, computational

modeling, and experiment.” (Kitano 2002)

• Modeling process– Wiring diagram of a biochemical reaction network.– Set of ODEs.– Assign values to entities in the model.– Use simulator to solve equations and adjust model

if needed.

Wiring Diagram

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Motivation

• Incompatibility problems– Manually re-encoding model in each tool– When simulators do not support models

developed in older systems they become stranded and unusable.

– Published models have their own set of instructions for obtaining model definitions. Authors use different modeling environments and model representation languages, this results in model definitions not being straightforward to examine, test and reuse.

Approach

• Inability to exchange models between different simulation and analysis tools because of a lack of a common format for describing models.

• Software Platforms for Systems Biology forum decided on developing simple XML-based language for representing and exchanging models between simulation/analysis tools.– Birth of Systems Biology Markup Language in April

2000.

SBML Language Specifics

• XML based language– eXtensible Markup Language.– Portability and increasingly widespread acceptance as

a standard data language for bioinformatics.

• SBML defined using UML– Unified Modeling Language.– UML used to define a representation in SBML.

• Base definition of SBML– Common features in representation languages from

simulators + information required to support biochemical models.

Introduction

• Modelers are NOT intended to write their models in SBML by hand.

• Software tools will read/write the format.• SBML releases referred to as Levels.

– Depending on features requested by community.

– Features voted on via sbml-discuss

• SBML language details.

SBML Overview

• Chemical reactions can be broken down into a number of elements.– Reactant species– Product species– Reactions– Stoichiometries– Rate laws– Parameters in the rate law.

• Additional components needed:– Compartments – Units (optional)

Components in an SBML Document

• An SBML Model consists of lists of one of more of the components:

– Compartment - Bounded space in which species are located.

– Species - Chemical entities that take part in reactions.

– Reaction - Represents any transformation, transport or binding process in a chemical reaction that can change the amount of one or more species.

– Parameter - Constant value variable for use in mathematical formulae.

SBML Components

• Components cont’d:– Unit Definition - Defines reusable units for the

model.– Rule - Provide a way to create constraints on

variables for cases in which constraints cannot be expressed using reactions nor the assignment of an initial value.

– Events (Level 2) - Describes time and form of explicit instantaneous discontinuous state changes in the model.

– Function Definition (Level 2) - associates identifier with a function definition (reuse).

SBML Parsers

• SBML code.• XML Parsers.

– Drawbacks - Too general

• Specialized SBML Parsers.– Need to understand the underlying biology– 2 parsers in the community

• JigCell SBML parser (Virginia Tech)• libSBML (Cal Tech)

Sample Model

• Biochemical control system for MPF activation of frog egg extracts.

• Zwolak, Jason W., Tyson, JJ, and Watson, LT.“Parameter Estimation. In a Cell Cycle Model for Frog Egg Extracts.” Journal of Computational Biology, Feb 2005, Vol. 12, No. 1: 48-63.

Sample Model - Wiring Diagram

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Sample Model - Differential Equations

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Future of SBML

• Currently on L2v2.• Proposals in the works for L3:

– Controlled Vocabularies• Vocabularies for labeling models and their components.

– Model Composition• Extensions to define an SBML model as a composition of

submodels.

– Hybrid Models• Multiple formalisms within the same model, such as continuous

and discrete.

– Complexes• Species with multiple states, like phosphorylated/not-

phosphorylated.

Comments and Questions