SBML: What Is It About?
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SBML: What Is It About?

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General overview of SBML given during HCLS SysBio telecon on June 6, 2012.

General overview of SBML given during HCLS SysBio telecon on June 6, 2012.

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  • computational methods, simulation, analysis are all an integral part\n
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  • Must weave solutions using different methods & tools\n
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  • a format that’s not any particular software systems’ internal format, but could act as a lingua franca that allows different software tools to exchange model definitions via this intermediate format, SBML\n
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  • compatible: either a count of things, or an extensive property such as concentration or density\n\nincompatible: activity level\n
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  • These models all have the common feature that they involve unitary entities related by equations that determine their quantities. There are no spatial effects, and also, all flat models -- single file. These are limitations and we’re working toward expanding SBML to remove those limitations.\n
  • These models all have the common feature that they involve unitary entities related by equations that determine their quantities. There are no spatial effects, and also, all flat models -- single file. These are limitations and we’re working toward expanding SBML to remove those limitations.\n
  • These models all have the common feature that they involve unitary entities related by equations that determine their quantities. There are no spatial effects, and also, all flat models -- single file. These are limitations and we’re working toward expanding SBML to remove those limitations.\n
  • These models all have the common feature that they involve unitary entities related by equations that determine their quantities. There are no spatial effects, and also, all flat models -- single file. These are limitations and we’re working toward expanding SBML to remove those limitations.\n
  • Evolution of features took time & practical experience\n
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  • a lot of tools work only at this level, but other tools such as virtual cell and databases that are more sophisticated need additional information about a model\n
  • a lot of tools work only at this level, but other tools such as virtual cell and databases that are more sophisticated need additional information about a model\n
  • a lot of tools work only at this level, but other tools such as virtual cell and databases that are more sophisticated need additional information about a model\n
  • a lot of tools work only at this level, but other tools such as virtual cell and databases that are more sophisticated need additional information about a model\n
  • a lot of tools work only at this level, but other tools such as virtual cell and databases that are more sophisticated need additional information about a model\n
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  • suppose you have a large number of models. it might be interesting to find out how they are related. this might not be obvious from the notes in the models or information provided by the creators -- the authors might not have known about other models that deal with a similar topic\n
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  • additional work to address more of what’s missing has been something that a growing community of people has been actively working on for many years\n\n
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  • corrections:\nadded missing dependencies on software\n\n
  • This question included an “other”, but only 3 checked it\n
  • This question included an “other”, but only 3 checked it\n
  • This question included an “other”, but only 3 checked it\n
  • This question included an “other”, but only 3 checked it\n
  • Question had “other”\nMost common response:- FBA\n2nd most common: not applicble (for conv tools)\n
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SBML: What Is It About? SBML: What Is It About? Presentation Transcript

  • SBML: What Is It About? Michael Hucka, Ph.D. Department of Computing + Mathematical Sciences California Institute of Technology Pasadena, CA, USAEmail: mhucka@caltech.edu Twitter: @mhucka HCLS Systems Biology, June 2012
  • General background and motivations Brief summary of SBML featuresOutline Annotations, connections and semantics SBML development today Acknowledgments
  • General background and motivations Brief summary of SBML featuresOutline Annotations, connections and semantics SBML development today Acknowledgments
  • Research today: experimentation, modeling, cogitation
  • One example of a type of model represented in SBML Simulation output Tyson et al. (1991) PNAS 88(1):7328–32
  • Must weave solutions from many methods and tools
  • Different tools different interfaces & languages
  • General background and motivations Brief summary of SBML featuresOutline Annotations, connections and semantics SBML development today Acknowledgments
  • SBML = Systems Biology Markup LanguageFormat for representing computational models of biological processes • Data structures + usage principles + serialization to XMLNeutral 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
  • so A li ftw ng ar ua e ( fra no nca t h fo um r an s)
  • The process is central • Called a “reaction” in SBML • Participants are pools of entities (species)Models can further include: • Unit definitions • Other constants & variables • Annotations • Compartments • Explicit math • Discontinuous events Basic SBML concepts are fairly simple
  • Well-stirred compartments c n
  • Species pools are located in compartments c protein A protein B n gene mRNAn mRNAc
  • Reactions can involve any species anywhere c protein A protein B n gene mRNAn mRNAc
  • Reactions can cross compartment boundaries c protein A protein B n gene mRNAn mRNAc
  • Reaction/process rates can be (almost) arbitrary formulas c protein A f1(x) protein B n f5(x) f2(x) gene f4(x) mRNAn f3(x) mRNAc
  • “Rules”: equations expressing relationships in addition to reaction sys.g1(x) cg2(x) protein A f1(x) protein B . . . n f5(x) f2(x) gene f4(x) mRNAn f3(x) mRNAc
  • “Events”: discontinuous actions triggered by system conditionsg1(x) cg2(x) protein A f1(x) protein B . . . n f5(x) f2(x) gene f4(x) mRNAn f3(x) mRNAc Event1: when (...condition...), Event2: when (...condition...), ... do (...assignments...) do (...assignments...)
  • Annotations: machine-readable semantics and links to other resources “This is identified “This is an enzymatic cg1(x)by GO id # ...” reaction with EC # ...”g2(x) . protein A f1(x) protein B . “This is a transport . n into the nucleus ...” “This compartment represents the nucleus ...” f5(x) f2(x) gene f4(x) mRNAn f3(x) mRNAc “This event represents ...” Event1: when (...condition...), Event2: when (...condition...), ... do (...assignments...) do (...assignments...)
  • 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 Find BioM exam ples in • Signaling pathway models http: odels Data base • Conductance-based models //bio mod els.ne t/bio • Neural models m odels • Pharmacokinetic/dynamics models • Infectious diseases Scope of SBML encompasses many types of models
  • Today: spatially homogeneous models • Metabolic network models Find BioM exam ples in • Signaling pathway models http: odels Data base • Conductance-based models //bio mod els.ne t/bio • Neural models m odels • Pharmacokinetic/dynamics models • Infectious diseasesComing: SBML Level 3 packages to support other types • E.g.: Spatially inhomogeneous models, also qualitative/logical Scope of SBML encompasses many types of models
  • SBML Level 1 SBML Level 2 SBML Level 3predefined math functions user-defined functions user-defined functionstext-string math notation MathML subset MathML subsetreserved namespaces for no reserved namespaces no reserved namespaces annotations for annotations for annotationsno controlled annotation RDF-based controlled RDF-based controlled scheme annotation scheme annotation scheme no discrete events discrete events discrete events default values defined default values defined no default values monolithic monolithic modular
  • General background and motivations Brief summary of SBML featuresOutline Annotations, connections and semantics SBML development today Acknowledgments
  • SBML provides syntax and only limited semantics
  • SBML provides syntax and only limited semanticsNo standard identifiers
  • SBML provides syntax and only limited semantics Low info contentNo standard identifiers
  • SBML provides syntax and only limited semantics Raw models alone are insufficient Need standard schemes for Low info machine-readable annotations content • For authorship, publication info • For links to other data resources • For semantics of mathematics Need common guidelines for minimal model quality and contentNo standard identifiers
  • SBML provides syntax and only limited semantics Raw models alone are insufficient Need standard schemes for Low info machine-readable annotations content • For authorship, publication info Defined •byFor links to other data resources SBML • For semantics of mathematics Need common guidelines for minimal model quality and contentNo standard identifiers
  • SBML provides syntax and only limited semantics Raw models alone are insufficient Need standard schemes for Low info machine-readable annotations content • For authorship, publication info Defined •byFor links to other dataDefined SBML resources by MIRIAM • For semantics of mathematics Need common guidelines for minimal model quality and contentNo standard identifiers
  • Linking SBML elements to external resources } In SBML Level 2–3, MIRIAM annotations are restricted to this specific form and to appear inside <annotation> elements. (Other RDF can appear elsewhere in <annotation>)
  • Linking SBML elements to external resources E.g.: species, compartment, reaction, parameter } In SBML Level 2–3, MIRIAM annotations are restricted to this specific form and to appear inside <annotation> elements. (Other RDF can appear elsewhere in <annotation>)
  • Linking SBML elements to external resources E.g.: species, compartment, reaction, parameter } Chosen from specific list— In SBML Level 2–3, http://sbml.org/miriam/qualifiers MIRIAM annotations E.g.: bqbiol:isPartOf are restricted to this specific form and to appear inside <annotation> elements. (Other RDF can appear elsewhere in <annotation>)
  • Linking SBML elements to external resources E.g.: species, compartment, reaction, parameter } Chosen from specific list— In SBML Level 2–3, http://sbml.org/miriam/qualifiers MIRIAM annotations E.g.: bqbiol:isPartOf are restricted to this specific form and to appear inside <annotation> Taken from public list at elements. http://sbml.org/miriam (Other RDF can appear elsewhere in <annotation>)
  • 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>
  • 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> Data references <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> Relationship qualifier <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>
  • BioModels Database: example of using the annotations
  • Resolving resource identifiersFor linking to data, need: • Globally unique, unambiguous identifiers • ... that are persistent despite resource changes (e.g., changed URLs) • ... that are maintained by the communityMIRIAM Registry provides data & identifiers.org provides resolvable URIs • Unlike URNs, can type identifiers.org URI in a web browserExample: • EC Code entry #1.1.1.1 - MIRIAM URN: urn:miriam:ec-code:1.1.1 - identifiers.org URI: http://identifiers.org/ec-code/1.1.1.1Developed by Nicolas Le Novère, Camille Laibe, Nick Juty @ EBI
  • General background and motivations Brief summary of SBML featuresOutline Annotations, connections and semantics SBML development today Acknowledgments
  • SBML Level 3: Supporting more categories of models Package W Package X Package Y Package Z SBML Level 3 Core (dependencies)A package adds constructs & capabilitiesModels declare which packages they use • Applications tell users which packages they supportPackage development can be decoupled
  • Find out more at http://sbml.org/Community/Wiki
  • Find software in the SBML Software Guide
  • Find software in the SBML Software Guide Find SBML software
  • Model Procedures ResultsRepresentation format SBRML Minimal info ? requirements Semantics— Mathematical Other annotations annotations annotationsGrowing ecosystem of standards to improve reproducibility
  • General background and motivations Brief summary of SBML featuresOutline Annotations, connections and semantics SBML development today Acknowledgments
  • People on SBML Team & BioModels.net Team SBML Team BioModels.net Team Michael Hucka Nicolas Le Novère Sarah Keating Camille LaibeFrank Bergmann Nicolas Rodriguez Lucian Smith Nick JutyNicolas Rodriguez Vijayalakshmi Chelliah Linda Taddeo Stuart Moodie Akiya Joukarou Visionaries Sarah Keating Akira Funahashi Hiroaki Kitano Maciej Swat Kimberley Begley John Doyle Lukas Endler Bruce Shapiro Chen Li Andrew Finney Harish Dharuri Ben Bornstein Lu Li Ben Kovitz Enuo He Hamid Bolouri Mélanie Courtot Herbert Sauro Alexander Broicher Jo Matthews Arnaud Henry Maria Schilstra Marco Donizelli
  • National Institute of General Medical Sciences (USA) fu We a ndEuropean Molecular Biology Laboratory (EMBL) ♥ ge ingELIXIR (UK) ou ie r sBeckman Institute, Caltech (USA) ncKeio 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)
  • Attendees at SBML 10th Anniversary Symposium, Edinburgh, 2010A huge thank you to the community
  • SBML http://sbml.org BioModels Database http://biomodels.net/biomodels identifiers.org http://identifiers.org MIRIAM http://biomodels.net/miriamURLs 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
  • I’d like your feedback!You can use this anonymous form: http://tinyurl.com/mhuckafeedback
  • Extra slides
  • Computational modeling has gained broad appeal Metabolic 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 2008Signalling pathways: Bray et al. Receptor clustering as a cellular mechanism to control sensitivity. Nature 1998; Bhallaad Iyengar. Emergent properties of signaling pathways. Science 1998; Schoeberl et al. Computational modeling of thedynamics 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 amitogen-activated protein kinase signaling network. Science 2002; Nelson et al. Oscillations in NF-κB Signaling Controlthe Dynamics of Gene Expression. Science 2004; Werner et al. Stimulus specificity of gene expression programsdetermined by temporal control of IKK activity. Science 2005; Sasagawa et al. Prediction and validation of the distinctdynamics of transient and sustained ERK activation. Nat Cell Biol 2005; Basak et al. A fourth IkappaB protein within theNF-κB signaling module. Cell 2007; McLean et al. Cross-talk and decision making in MAP kinase pathways. Nat Genet2007; Ashall et al. Pulsatile Stimulation Determines Timing and Specificity of NF-κB-Dependent Transcription. Science2009; Becker et al. Covering a broad dynamic range: information processing at the erythropoietin receptor. Science 2010Gene 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 Dassowet al. The segment polarity network is a robust developmental module. Nature 2000; Elowitz and Leibler. A syntheticoscillatory network of transcriptional regulators. Nature 2000; Shen-Orr et al, Network motifs in the transcriptionalregulation 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 2009Pharmacometrics models: Labrijn et al. Therapeutic IgG4 antibodies engage in Fab-arm exchange with endogenoushuman IgG4 in vivo. Nat Biotechnol 2009Physiological models: Noble. Modeling the heart from genes to cells to the whole organ. Science 2002; Izhikevich andEdelman. Large-scale model of mammalian thalamocortical systems. PNAS 2008Infectious diseases: Perelson et al. HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viralgeneration time. Science 1996; Nowak. Population dynamics of immune responses to persistent viruses. Science 1996;
  • Software tools survey 2011
  • General features of the surveyOnline, implemented using commercial survey website28 questions • Mix of multiple choice and fill-in-the-blank85 responses by July 2011 • Removed incomplete responses • 81 software tools leftAvoided “corrections” to data
  • Purposes of the software systems Question: Which of the following categories best describe your software? (Check all that apply.) Simulation software 42Analysis s/w (in addition, or instead of, simulation) 40 Creation/model development software 31 Visualization/display/formatting software 31 Utility software (e.g., format conversion) 23 Data integration and management software 16 Repository or database 14 Framework or library (for use in developing s/w) 13 S/w for interactive env. (e.g., MATLAB, R, ...) 13 Annotation software 11 0 20 40 60 80 Total number of software tools
  • Purposes of the software systems Question: Which of the following categories best describe your software? (Check all that apply.) Simulation software 42Analysis s/w (in addition, or instead of, simulation) 40 Creation/model development software 31 Visualization/display/formatting software 31 Utility software (e.g., format conversion) 23 Data integration and management software 16 Repository or database 14 Framework or library (for use in developing s/w) 13 S/w for interactive env. (e.g., MATLAB, R, ...) 13 Annotation software 11 0 20 40 60 80 Total number of software tools
  • Purposes of the software systems Question: Which of the following categories best describe your software? (Check all that apply.) Simulation software 42Analysis s/w (in addition, or instead of, simulation) 40 Creation/model development software 31 Visualization/display/formatting software 31 Utility software (e.g., format conversion) 23 Data integration and management software 16 Repository or database 14 Framework or library (for use in developing s/w) 13 1/4 1/2 3/4 S/w for interactive env. (e.g., MATLAB, R, ...) 13 Annotation software 11 0 20 40 60 80 Total number of software tools
  • Purposes of the software systems Question: Which of the following categories best describe your software? (Check all that apply.) Simulation software 42Analysis s/w (in addition, or instead of, simulation) 40 Creation/model development software 31 Visualization/display/formatting software 31 Utility software (e.g., format conversion) 23 Data integration and management software 16 Repository or database 14 Framework or library (for use in developing s/w) 13 S/w for interactive env. (e.g., MATLAB, R, ...) 13 Annotation software 11 0 20 40 60 80 Total number of software tools
  • Mathematical frameworksQuestion: Regardless of whether your software provides simulationcapabilities, what modeling frameworks does the package support whenworking with SBML files? Ordinary differential equations (ODE) 54 Discrete stochastic simulation 28 Discontinuous event handling 25 Differential-algebraic equations (DAE) 17 Logical/Boolean networks 11 Delay-differential equations (DDE) 9 Partial differential equations (PDE) 8None of the above, or other framework 20 0 20 40 60 80 Total number of software tools
  • Mathematical frameworksQuestion: Regardless of whether your software provides simulationcapabilities, what modeling frameworks does the package support whenworking with SBML files? Ordinary differential equations (ODE) 54 Discrete stochastic simulation 28 Discontinuous event handling 25 Differential-algebraic equations (DAE) 17 Logical/Boolean networks 11 Delay-differential equations (DDE) 9 Partial differential equations (PDE) 8None of the above, or other framework 20 E.g.: FBA 0 20 40 60 80 Total number of software tools
  • Other supported standardsQuestion: Which other standards does your software support? MIRIAM 16 SBO 14 SBGN 13 BioPAX 6 CellML 3 SED-ML 3 MFAML 1 PNML 1 (Warning: SBOL 1 different scale) 0 5 10 15 20 Total # software tools supporting other standards
  • Availability of softwareFee-based Not Fee-based 2% avail. 10% 21% Code Free Free available 98% 90% 79% Fees for Fees for non- Is source codeacademics academics available?