sbml: what is it about?
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SBML: What Is It About?Michael Hucka, Ph.D.
Department of Computing + Mathematical SciencesCalifornia Institute of Technology
Pasadena, CA, USA
HCLS Systems Biology, June 2012
Email: mhucka@caltech.edu Twitter: @mhucka
Outli
ne
General background and motivations
Brief summary of SBML features
Annotations, connections and semantics
SBML development today
Acknowledgments
Outli
ne
General background and motivations
Brief summary of SBML features
Annotations, connections and semantics
SBML development today
Acknowledgments
Research today: experimentation, modeling, cogitation
One example of a type of model represented in SBML
Tyson et al. (1991) PNAS 88(1):7328–32
Simulationoutput
Must weave solutions from many methods and tools
Different tools ⇒ different interfaces & languages
Outli
ne
General background and motivations
Brief summary of SBML features
Annotations, connections and semantics
SBML development today
Acknowledgments
Format for representing computational models of biological processes
• Data structures + usage principles + serialization to XML
Neutral with respect to modeling framework
• E.g., ODE, stochastic systems, etc.
Development started in 2000, with first specification distributed in 2001
• XML was still relatively new, RDF even more so
SBML = Systems Biology Markup Language
A lingua fra
nca for
software
(not humans)
The process is central
• Called a “reaction” in SBML
• Participants are pools of entities (species)
Models can further include:
• Other constants & variables
• Compartments
• Explicit math
• Discontinuous events
Basic SBML concepts are fairly simple
• Unit definitions
• Annotations
Well-stirred compartments
c
n
Species pools are located in compartments
c
n
protein A protein B
gene mRNAn mRNAc
Reactions can involve any species anywhere
c
n
protein A protein B
gene mRNAn mRNAc
Reactions can cross compartment boundaries
c
n
protein A protein B
gene mRNAn mRNAc
Reaction/process rates can be (almost) arbitrary formulas
c
n
protein A protein B
gene mRNAn mRNAc
f1(x)
f2(x)
f3(x)f4(x)
f5(x)
“Rules”: equations expressing relationships in addition to reaction sys.
c
n
protein A protein B
gene mRNAn mRNAc
f1(x)
f2(x)
f3(x)
g1(x)g2(x)
.
.
.
f4(x)
f5(x)
“Events”: discontinuous actions triggered by system conditions
c
n
protein A protein B
gene mRNAn mRNAc
f1(x)
f2(x)
f3(x)
g1(x)g2(x)
.
.
.
Event1: when (...condition...), do (...assignments...)
Event2: when (...condition...), do (...assignments...)
...
f4(x)
f5(x)
Annotations: machine-readable semantics and links to other resources
Event1: when (...condition...), do (...assignments...)
Event2: when (...condition...), do (...assignments...)
...
c
n
protein A protein B
gene mRNAn mRNAc
f1(x)
f2(x)
f3(x)
g1(x)g2(x)
.
.
.
f4(x)
f5(x)
“This event represents ...”
“This is identified by GO id # ...”
“This is an enzymatic reaction with EC # ...”
“This is a transport into the nucleus ...” “This compartment
represents the nucleus ...”
Scope of SBML encompasses many types of models
Today: spatially homogeneous models
• Metabolic network models
• Signaling pathway models
• Conductance-based models
• Neural models
• Pharmacokinetic/dynamics models
• Infectious diseases
Scope of SBML encompasses many types of models
Today: spatially homogeneous models
• Metabolic network models
• Signaling pathway models
• Conductance-based models
• Neural models
• Pharmacokinetic/dynamics models
• Infectious diseases
Scope of SBML encompasses many types of models
Find examples inBioModels Databasehttp://biomodels.net/biomodels
Today: spatially homogeneous models
• Metabolic network models
• Signaling pathway models
• Conductance-based models
• Neural models
• Pharmacokinetic/dynamics models
• Infectious diseases
Coming: SBML Level 3 packages to support other types
• E.g.: Spatially inhomogeneous models, also qualitative/logical
Scope of SBML encompasses many types of models
Find examples inBioModels Databasehttp://biomodels.net/biomodels
SBML Level 1 SBML Level 2 SBML Level 3
predefined math functions user-defined functions user-defined functions
text-string math notation MathML subset MathML subset
reserved namespaces for annotations
no reserved namespaces for annotations
no reserved namespaces for annotations
no controlled annotation scheme
RDF-based controlled annotation scheme
RDF-based controlled annotation scheme
no discrete events discrete events discrete events
default values defined default values defined no default values
monolithic monolithic modular
Outli
ne
General background and motivations
Brief summary of SBML features
Annotations, connections and semantics
SBML development today
Acknowledgments
SBML provides syntax and only limited semantics
SBML provides syntax and only limited semantics
No standard identifiers
SBML provides syntax and only limited semantics
Low info content
No standard identifiers
Raw models alone are insufficient
Need standard schemes for machine-readable annotations
• For authorship, publication info
• For links to other data resources
• For semantics of mathematics
Need common guidelines for minimal model quality and content
SBML provides syntax and only limited semantics
Low info content
No standard identifiers
Raw models alone are insufficient
Need standard schemes for machine-readable annotations
• For authorship, publication info
• For links to other data resources
• For semantics of mathematics
Need common guidelines for minimal model quality and content
SBML provides syntax and only limited semantics
Low info content
No standard identifiers
Definedby SBML
Raw models alone are insufficient
Need standard schemes for machine-readable annotations
• For authorship, publication info
• For links to other data resources
• For semantics of mathematics
Need common guidelines for minimal model quality and content
SBML provides syntax and only limited semantics
Low info content
No standard identifiers
Definedby MIRIAM
Definedby SBML
Linking SBML elements to external resources
}In SBML Level 2–3, MIRIAM annotationsare restricted to this specific form and to appear inside <annotation> elements.
(Other RDF can appear elsewhere in <annotation>)
Linking SBML elements to external resources
}In SBML Level 2–3, MIRIAM annotationsare restricted to this specific form and to appear inside <annotation> elements.
(Other RDF can appear elsewhere in <annotation>)
E.g.: species, compartment, reaction, parameter
Linking SBML elements to external resources
}In SBML Level 2–3, MIRIAM annotationsare restricted to this specific form and to appear inside <annotation> elements.
(Other RDF can appear elsewhere in <annotation>)
E.g.: species, compartment, reaction, parameter
Chosen from specific list—http://sbml.org/miriam/qualifiersE.g.: bqbiol:isPartOf
Linking SBML elements to external resources
}In SBML Level 2–3, MIRIAM annotationsare restricted to this specific form and to appear inside <annotation> elements.
(Other RDF can appear elsewhere in <annotation>)
E.g.: species, compartment, reaction, parameter
Chosen from specific list—http://sbml.org/miriam/qualifiersE.g.: bqbiol:isPartOf
Taken from public list athttp://sbml.org/miriam
<species metaid="metaid_0000009" id="species_3" compartment="c_1"> <annotation> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bqbiol="http://biomodels.net/biology-qualifiers/" > <rdf:Description rdf:about="#metaid_0000009"> <bqbiol:is> <rdf:Bag> <rdf:li rdf:resource="urn:miriam:obo.chebi:CHEBI%3A15996"/> <rdf:li rdf:resource="urn:miriam:kegg.compound:C00044"/> </rdf:Bag> </bqbiol:is> </rdf:Description> </rdf:RDF> </annotation> </species>
Example
<species metaid="metaid_0000009" id="species_3" compartment="c_1"> <annotation> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bqbiol="http://biomodels.net/biology-qualifiers/" > <rdf:Description rdf:about="#metaid_0000009"> <bqbiol:is> <rdf:Bag> <rdf:li rdf:resource="urn:miriam:obo.chebi:CHEBI%3A15996"/> <rdf:li rdf:resource="urn:miriam:kegg.compound:C00044"/> </rdf:Bag> </bqbiol:is> </rdf:Description> </rdf:RDF> </annotation> </species>
<rdf:Bag> <rdf:li rdf:resource="urn:miriam:obo.chebi:CHEBI%3A15996"/> <rdf:li rdf:resource="urn:miriam:kegg.compound:C00044"/> </rdf:Bag>
Data references
Example
<species metaid="metaid_0000009" id="species_3" compartment="c_1"> <annotation> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bqbiol="http://biomodels.net/biology-qualifiers/" > <rdf:Description rdf:about="#metaid_0000009"> <bqbiol:is> <rdf:Bag> <rdf:li rdf:resource="urn:miriam:obo.chebi:CHEBI%3A15996"/> <rdf:li rdf:resource="urn:miriam:kegg.compound:C00044"/> </rdf:Bag> </bqbiol:is> </rdf:Description> </rdf:RDF> </annotation> </species>
<bqbiol:is>
</bqbiol:is>
Relationship qualifier
Example
BioModels Database: example of using the annotations
Resolving resource identifiers
For linking to data, need:
• Globally unique, unambiguous identifiers
• ... that are persistent despite resource changes (e.g., changed URLs)
• ... that are maintained by the community
MIRIAM Registry provides data & identifiers.org provides resolvable URIs
• Unlike URNs, can type identifiers.org URI in a web browser
Example:
• EC Code entry #1.1.1.1
- MIRIAM URN: urn:miriam:ec-code:1.1.1
- identifiers.org URI: http://identifiers.org/ec-code/1.1.1.1
Developed by Nicolas Le Novère, Camille Laibe, Nick Juty @ EBI
Outli
ne
General background and motivations
Brief summary of SBML features
Annotations, connections and semantics
SBML development today
Acknowledgments
SBML Level 3 Core
Package X Package Y Package Z
Package W
(dependencies)
SBML Level 3: Supporting more categories of models
A package adds constructs & capabilities
Models declare which packages they use
• Applications tell users which packages they support
Package development can be decoupled
Find out more at http://sbml.org/Community/Wiki
Find software in the SBML Software Guide
Find SBML software
Find software in the SBML Software Guide
Representationformat
Model Procedures Results
Minimal inforequirements
Semantics—
Mathematical
Other
SBRML
?
annotations annotations annotations
Growing ecosystem of standards to improve reproducibility
Outli
ne
General background and motivations
Brief summary of SBML features
Annotations, connections and semantics
SBML development today
Acknowledgments
SBML Team BioModels.net TeamMichael Hucka Nicolas Le NovèreSarah Keating Camille Laibe
Frank Bergmann Nicolas RodriguezLucian Smith Nick Juty
Nicolas Rodriguez Vijayalakshmi ChelliahLinda Taddeo Stuart MoodieAkiya Joukarou Sarah KeatingAkira Funahashi Maciej Swat
Kimberley Begley Lukas EndlerBruce Shapiro Chen Li
Andrew Finney Harish DharuriBen Bornstein Lu Li
Ben Kovitz Enuo HeHamid Bolouri Mélanie CourtotHerbert Sauro Alexander BroicherJo Matthews Arnaud Henry
Maria Schilstra Marco Donizelli
VisionariesHiroaki Kitano
John Doyle
People on SBML Team & BioModels.net Team
National Institute of General Medical Sciences (USA) European Molecular Biology Laboratory (EMBL)ELIXIR (UK)Beckman Institute, Caltech (USA)Keio University (Japan)JST ERATO Kitano Symbiotic Systems Project (Japan) (to 2003)JST ERATO-SORST Program (Japan)International Joint Research Program of NEDO (Japan)Japanese Ministry of AgricultureJapanese Ministry of Educ., Culture, Sports, Science and Tech.
BBSRC (UK)National Science Foundation (USA)DARPA IPTO Bio-SPICE Bio-Computation Program (USA)Air Force Office of Scientific Research (USA)STRI, University of Hertfordshire (UK)Molecular Sciences Institute (USA)
We ♥ our
funding agencies
A huge thank you to the communityAttendees at SBML 10th Anniversary Symposium, Edinburgh, 2010
SBML http://sbml.org
BioModels Database http://biomodels.net/biomodels
identifiers.org http://identifiers.org
MIRIAM http://biomodels.net/miriam
MIASE http://biomodels.net/miase
SED-ML http://biomodels.net/sed-ml
SBO http://biomodels.net/sbo
SBRML http://tinyurl.com/sbrml
SBGN http://sbgn.org
URLs
I’d like your feedback!You can use this anonymous form:
http://tinyurl.com/mhuckafeedback
Extra slides
Computational modeling has gained broad appealMetabolic networks: Fung et al. A synthetic gene-metabolic oscillator. Nature 2005; Herrgård et al. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nat Biotechnol 2008
Signalling pathways: Bray et al. Receptor clustering as a cellular mechanism to control sensitivity. Nature 1998; Bhalla ad Iyengar. Emergent properties of signaling pathways. Science 1998; Schoeberl et al. Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Nat Biotechnol 2002; Hoffmann et. The IκB-NF-κB signaling module: temporal control and selective gene activation. Science 2002; Smith et al. Systems analysis of Ran transport. Science 2002; Bhalla et al. MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network. Science 2002; Nelson et al. Oscillations in NF-κB Signaling Control the Dynamics of Gene Expression. Science 2004; Werner et al. Stimulus specificity of gene expression programs determined by temporal control of IKK activity. Science 2005; Sasagawa et al. Prediction and validation of the distinct dynamics of transient and sustained ERK activation. Nat Cell Biol 2005; Basak et al. A fourth IkappaB protein within the NF-κB signaling module. Cell 2007; McLean et al. Cross-talk and decision making in MAP kinase pathways. Nat Genet 2007; Ashall et al. Pulsatile Stimulation Determines Timing and Specificity of NF-κB-Dependent Transcription. Science 2009; Becker et al. Covering a broad dynamic range: information processing at the erythropoietin receptor. Science 2010
Gene regulatory networks: McAdams and Shapiro. Circuit simulation of genetic networks. Science 1995; Yue et al. Genomic cis-regulatory logic: Experimental and computational analysis of a sea urchin gene. Science 1998; Von Dassow et al. The segment polarity network is a robust developmental module. Nature 2000; Elowitz and Leibler. A synthetic oscillatory network of transcriptional regulators. Nature 2000; Shen-Orr et al, Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet 2002; Yao et al. A bistable Rb-E2F switch underlies the restriction point. Nat Cell Biol 2008; Friedland. Synthetic gene networks that count. Science 2009
Pharmacometrics models: Labrijn et al. Therapeutic IgG4 antibodies engage in Fab-arm exchange with endogenous human IgG4 in vivo. Nat Biotechnol 2009
Physiological models: Noble. Modeling the heart from genes to cells to the whole organ. Science 2002; Izhikevich and Edelman. Large-scale model of mammalian thalamocortical systems. PNAS 2008
Infectious diseases: Perelson et al. HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time. Science 1996; Nowak. Population dynamics of immune responses to persistent viruses. Science 1996;
Software tools survey 2011
General features of the survey
Online, implemented using commercial survey website
28 questions
• Mix of multiple choice and fill-in-the-blank
85 responses by July 2011
• Removed incomplete responses
• 81 software tools left
Avoided “corrections” to data
Question: Which of the following categories best describe your software? (Check all that apply.)
Purposes of the software systems
Total number of software tools
Simulation software
Analysis s/w (in addition, or instead of, simulation)
Creation/model development software
Visualization/display/formatting software
Utility software (e.g., format conversion)
Data integration and management software
Repository or database
Framework or library (for use in developing s/w)
S/w for interactive env. (e.g., MATLAB, R, ...)
Annotation software0 20 40 60 80
11
13
13
14
16
23
31
31
40
42
Question: Which of the following categories best describe your software? (Check all that apply.)
Purposes of the software systems
Total number of software tools
Simulation software
Analysis s/w (in addition, or instead of, simulation)
Creation/model development software
Visualization/display/formatting software
Utility software (e.g., format conversion)
Data integration and management software
Repository or database
Framework or library (for use in developing s/w)
S/w for interactive env. (e.g., MATLAB, R, ...)
Annotation software0 20 40 60 80
11
13
13
14
16
23
31
31
40
42
Question: Which of the following categories best describe your software? (Check all that apply.)
Purposes of the software systems
Total number of software tools
Simulation software
Analysis s/w (in addition, or instead of, simulation)
Creation/model development software
Visualization/display/formatting software
Utility software (e.g., format conversion)
Data integration and management software
Repository or database
Framework or library (for use in developing s/w)
S/w for interactive env. (e.g., MATLAB, R, ...)
Annotation software0 20 40 60 80
11
13
13
14
16
23
31
31
40
42
1/4 1/2 3/4
Question: Which of the following categories best describe your software? (Check all that apply.)
Purposes of the software systems
Total number of software tools
Simulation software
Analysis s/w (in addition, or instead of, simulation)
Creation/model development software
Visualization/display/formatting software
Utility software (e.g., format conversion)
Data integration and management software
Repository or database
Framework or library (for use in developing s/w)
S/w for interactive env. (e.g., MATLAB, R, ...)
Annotation software0 20 40 60 80
11
13
13
14
16
23
31
31
40
42
Question: Regardless of whether your software provides simulation capabilities, what modeling frameworks does the package support when working with SBML files?
Mathematical frameworks
Ordinary differential equations (ODE)
Discrete stochastic simulation
Discontinuous event handling
Differential-algebraic equations (DAE)
Logical/Boolean networks
Delay-differential equations (DDE)
Partial differential equations (PDE)
None of the above, or other framework0 20 40 60 80
20
8
9
11
17
25
28
54
Total number of software tools
Question: Regardless of whether your software provides simulation capabilities, what modeling frameworks does the package support when working with SBML files?
Mathematical frameworks
Ordinary differential equations (ODE)
Discrete stochastic simulation
Discontinuous event handling
Differential-algebraic equations (DAE)
Logical/Boolean networks
Delay-differential equations (DDE)
Partial differential equations (PDE)
None of the above, or other framework0 20 40 60 80
20
8
9
11
17
25
28
54
Total number of software tools
E.g.: FBA
Other supported standards
MIRIAMSBO
SBGNBioPAXCellML
SED-MLMFAML
PNMLSBOL
0 5 10 15 20
111
33
613
1416
Total # software tools supporting other standards
(Warning: different scale)
Question: Which other standards does your software support?
Availability of software
Fee-based2%
Free98%
Fees for academics
Fee-based10%
Free90%
Fees for non-academics
Notavail.21%
Codeavailable
79%
Is source code available?
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