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Finding common ground between modelers and simulation software in systems biology

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Slides from presentation given at the Merging Knowledge workshop in Trento, Italy, December 2010.

Slides from presentation given at the Merging Knowledge workshop in Trento, Italy, December 2010.

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  • 1. Finding common ground between modelersand simulation software in systems biology Michael Hucka (On behalf of many people) Senior Research Fellow California Institute of Technology Pasadena, California, USA 2
  • 2. So much is known, and yet, not nearly enough... 3
  • 3. Must weave solutions using different methods & tools 4
  • 4. Common side-effect: compatibility problems 5
  • 5. Models represent knowledge to be exchanged 6
  • 6. SBML 7
  • 7. SBML = Systems Biology Markup LanguageFormat for representing computational models • Defines object model + rules for its use - Serialized to XMLNeutral with respect to modeling framework • ODE vs. stochastic vs. ...A lingua franca for software • Not procedural 8
  • 8. Basic SBML concepts are simpleThe reaction is central: a process occurring at a given rate • Participants are pools of entities (species) f ([A],[B],[P ],...) na A + nb B − − − − − − → np P −−−−−− f (...) nc C −− −→ nd D + ne E + nf F . . .Models can further include: • Other constants & variables • Unit definitions • Compartments • Annotations • Explicit math • Discontinuous events 9
  • 9. Basic SBML concepts are simpleThe reaction is central: a process occurring at a given rate • Participants are pools of entities (species) Can be anything conceptually f ([A],[B],[P ],...) na A + nb B − − − − − − → np P −−−−−− compatible f (...) nc C −− −→ nd D + ne E + nf F . . .Models can further include: • Other constants & variables • Unit definitions • Compartments • Annotations • Explicit math • Discontinuous events 9
  • 10. Signaling pathway models Fernandez et al. (2006) DARPP-32 Is a Robust Integrator of Dopamine and Glutamate Signals PLoS Computational Biology BioModels Database model #BIOMD0000000153 Scope of SBML is not limited to metabolic models 10
  • 11. Signaling pathway models Hodgkin & Huxley (1952) A quantitative description ofConductance-based models membrane current and its • application to conduction and “Rate rules” for temporal evolution excitation in nerve of quantitative parameters J. Physiology 117:500–544 BioModels Database model #BIOMD0000000020 Scope of SBML is not limited to metabolic models 11
  • 12. Signaling pathway models Izhikevich EM. (2003) Simple model of spiking neurons.Conductance-based models IEEE Trans Neural Net. • “Rate rules” for temporal evolution of quantitative parameters BioModels Database model #BIOMD0000000127Neural models • “Events” for discontinuous changes in quantitative parameters Scope of SBML is not limited to metabolic models 12
  • 13. Signaling pathway models Tham et al. (2008) A pharmacodynamic model forConductance-based models the time course of tumor shrinkage by gemcitabine + • “Rate rules” for temporal evolution of quantitative parameters carboplatin in non-small cell lung cancer patients Clin. Cancer Res. 14Neural models BioModels Database model • “Events” for discontinuous changes in quantitative parameters #BIOMD0000000234Pharmacokinetic/dynamics models • “Species” is not required to be a biochemical entity Scope of SBML is not limited to metabolic models 13
  • 14. Signaling pathway models Munz et al. (2009 )Conductance-based models When zombies attack!: Mathematical modelling of an • “Rate rules” for temporal evolution of quantitative parameters outbreak of zombie infection Infectious Disease Modelling Research Progress, eds. Tchuenche et al., p. 133–150Neural models • “Events” for discontinuous changes in quantitative parameters BioModels Database model #MODEL1008060001Pharmacokinetic/dynamics models • “Species” is not required to be a biochemical entityInfectious diseases Scope of SBML is not limited to metabolic models 14
  • 15. Number of software systems supporting SBML 205 as of Nov. 28 ↓ 200 150 100 50 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 (counted in middle of each year) 15
  • 16. Herrgård et al., Nature Biotech., 26:10, 2008 2342 reactions A consensus yeast metabolic network reconstruction © 2008 Nature Publishing Group http://www.nature.com/naturebiotechnology obtained from a community approach to systems biology Markus J Herrgård1,19,20, Neil Swainston2,3,20, Paul Dobson3,4, Warwick B Dunn3,4, K Yalçin Arga5, Mikko Arvas6, Nils Blüthgen3,7, Simon Borger8, Roeland Costenoble9, Matthias Heinemann9, Michael Hucka10, Nicolas Le Novère11, Peter Li2,3, Wolfram Liebermeister8, Monica L Mo1, Ana Paula Oliveira12, Dina Petranovic12,19, Stephen Pettifer2,3, Evangelos Simeonidis3,7, Kieran Smallbone3,13, Irena Spasić2,3, Dieter Weichart3,4, Roger Brent14, David S Broomhead3,13, Hans V Westerhoff 3,7,15, Betül Kırdar5, Merja Penttilä6, Edda Klipp8, Bernhard Ø Palsson1, Uwe Sauer9, Stephen G Oliver3,16, Pedro Mendes2,3,17, Jens Nielsen12,18 & Douglas B Kell*3,4 Genomic data allow the large-scale manual or semi-automated of their parameters. Armed with such information, it is then possible to assembly of metabolic network reconstructions, which provide provide a stochastic or ordinary differential equation model of the entire highly curated organism-specific knowledge bases. Although metabolic network of interest. An attractive feature of metabolism, for the several genome-scale network reconstructions describe purposes of modeling, is that, in contrast to signaling pathways, metabo- Saccharomyces cerevisiae metabolism, they differ in scope lism is subject to direct thermodynamic and (in particular) stoichiometric and content, and use different terminologies to describe the constraints3. Our focus here is on the first two stages of the reconstruction same chemical entities. This makes comparisons between them process, especially as it pertains to the mapping of experimental metabo- difficult and underscores the desirability of a consolidated lomics data onto metabolic network reconstructions. metabolic network that collects and formalizes the ‘community Besides being an industrial workhorse for a variety of biotechnological knowledge’ of yeast metabolism. We describe how we have products, S. cerevisiae is a highly developed model organism for biochemi- produced a consensus metabolic network reconstruction cal, genetic, pharmacological and post-genomic studies5. It is especially for S. cerevisiae. In drafting it, we placed special emphasis attractive because of the availability of its genome sequence6, a whole series on referencing molecules to persistent databases or using of bar-coded deletion7,8 and other9 strains, extensive experimental ’omics database-independent forms, such as SMILES or InChI strings, data10–14 and the ability to grow it for extended periods under highly con- as this permits their chemical structure to be represented trolled conditions15. The very active scientific community that works on unambiguously and in a manner that permits automated S. cerevisiae has a history of collaborative research projects that have led to reasoning. The reconstruction is readily available via a publicly substantial advances in our understanding of eukaryotic biology6,8,13,16,17. Model scale & complexity have been increasing accessible database and in the Systems Biology Markup Language (http://www.comp-sys-bio.org/yeastnet). It can be maintained as a resource that serves as a common denominator Furthermore, yeast metabolic physiology has been the subject of inten- sive study and most of the components of the yeast metabolic network are relatively well characterized. Taken together, these factors make yeast for studying the systems biology of yeast. Similar strategies metabolism an attractive topic to test a community approach to build 16
  • 17. Aho et al., PLoS One, May 14;5(5), 2010. 30,965 reactions! Today’s largest models are over 10x bigger! 17
  • 18. SBML continues to evolve 18
  • 19. SBML Level 3—A modular SBML Package Z Package X Package Y SBML Level 3 CoreA package adds constructs & capabilitiesModels declare which packages they use • Applications tell users which packages they supportPackage development can be decoupled 19
  • 20. Package Specification statusGraph layout Level 3 version defined; in reviewMulticomponent species Level 3 version defined; in reviewHierarchical composition Level 3 specification under discussionGroups Level 3 specification under discussionQualitative models Level 3 specification under discussionSpatial geometry Level 3 specification under discussionArrays & sets Specification proposedDistribution & ranges Specification proposedSteady-state models Specification proposedGraph rendering Specification proposedSpatial diffusion Specification neededDynamic structures Specification needed 20
  • 21. Package Specification statusGraph layout Level 3 version defined; in reviewMulticomponent species Level 3 version species to represent: Extends SBML defined; in review • Entities that can exist underHierarchical composition Level 3 specification under discussion different states affecting theirGroups behaviors Level 3 specification under discussion • Entities that are complexes ofQualitative models Level 3 specification under discussion other entitiesSpatial geometry Level 3 specification under discussionArrays & sets Specification proposedDistribution & ranges Specification proposedSteady-state models Specification proposedGraph rendering Specification proposedSpatial diffusion Specification neededDynamic structures Specification needed 20
  • 22. Package Specification statusGraph layout Level 3 version defined; in reviewMulticomponent species Level 3 version defined; in reviewHierarchical composition Models composed of submodels Level 3 specification under discussionGroups Level 3 specification under discussionQualitative models Level 3 specification under discussionSpatial geometry Level 3 specification under discussionArrays & sets Specification proposedDistribution & ranges Specification proposedSteady-state models Specification proposedGraph rendering Specification proposedSpatial diffusion Specification neededDynamic structures Specification needed 20
  • 23. Package Specification statusGraph layout Level 3 version defined; in reviewMulticomponent species Level 3 version defined; in reviewHierarchical composition Level 3 specification under discussion Grouping model entities together,Groups Level 3 specification under discussion for conceptual and annotationQualitative models Level 3 specification under discussion purposesSpatial geometry Level 3 specification under discussionArrays & sets Specification proposedDistribution & ranges Specification proposedSteady-state models Specification proposedGraph rendering Specification proposedSpatial diffusion Specification neededDynamic structures Specification needed 20
  • 24. Package Specification statusGraph layout Level 3 version defined; in reviewMulticomponent species Level 3 version defined; in reviewHierarchical composition Level 3 specification under discussionGroups Level 3 specification under discussion Models in which entity variables areQualitative models Levelquantities; e.g., boolean models not 3 specification under discussionSpatial geometry Level 3 specification under discussionArrays & sets Specification proposedDistribution & ranges Specification proposedSteady-state models Specification proposedGraph rendering Specification proposedSpatial diffusion Specification neededDynamic structures Specification needed 20
  • 25. Package Specification statusGraph layout Level 3 version defined; in reviewMulticomponent species Level 3 version defined; in reviewHierarchical composition Level 3 specification under discussionGroups Level 3 specification under discussionQualitative models Level 3 specification under discussion 2-D and 3-D geometry of physicalSpatial geometry Level 3 specification under discussion objects (compartments & species)Arrays & sets Specification proposedDistribution & ranges Specification proposedSteady-state models Specification proposedGraph rendering Specification proposedSpatial diffusion Specification neededDynamic structures Specification needed 20
  • 26. 21
  • 27. Is enough? 21
  • 28. Growing community, greater challenges 22
  • 29. Model Procedures ResultsRepresentation format SBRML Minimal info ? requirements Semantics— Mathematical Other annotations annotations annotations 23
  • 30. Model Procedures ResultsRepresentation format SBRML Minimal info ? requirements Semantics— Mathematical Other annotations annotations annotations 23
  • 31. Annotations add semantics and connectionsAnnotations can answer questions: • “What exactly is this entity you call X?” • “What other identities does this entity have?” • “What exactly is the process represented by equation ‘e17’?” • “What role does constant ‘k3’ play in equation ‘e17’?” • “What mathematical framework is being assumed?” • “What organism is this in?” • ... etc. ...Multiple annotations on same entity are common 24
  • 32. Systems Biology Ontology (SBO)For semantics of a model’s mathHuman- & program-accessible • Browser interface • Web servicesMath formulas in MathML 25
  • 33. Systems Biology Ontology (SBO)For semantics of a model’s mathHuman- & program-accessible • Browser interface • Web servicesMath formulas in MathML 25
  • 34. Systems Biology Ontology (SBO)For semantics of a model’s mathHuman- & program-accessible • Browser interface • Web servicesMath formulas in MathML 25
  • 35. <sbml ...> ... <listOfCompartments> <compartment id="cell" size="1e-15" /> </listOfCompartments> <listOfSpecies> <species compartment="cell" id="S1" initialAmount="1000" /> <species compartment="cell" id="S2" initialAmount="0" /> <listOfSpecies> <listOfParameters> <parameter id="k" value="0.005" sboTerm="SBO:0000339" /> <listOfParameters> <listOfReactions> <reaction id="r1" reversible="false"> <listOfReactants> <speciesReference species="S1" stoichiometry="2" sboTerm="SBO:0000010" /> </listOfReactants> <listOfProducts> <speciesReference species="S1" stoichiometry="2" sboTerm="SBO:0000011" /> </listOfProducts> <kineticLaw sboTerm="SBO:0000052"> <math> ... <math> ...</sbml> 26
  • 36. <sbml ...> ... <listOfCompartments> <compartment id="cell" size="1e-15" /> </listOfCompartments> <listOfSpecies> <species compartment="cell" id="S1" initialAmount="1000" /> <species compartment="cell" id="S2" initialAmount="0" /> <listOfSpecies> <listOfParameters> <parameter id="k" value="0.005" sboTerm="SBO:0000339" /> SBO:0000339 <listOfParameters> <listOfReactions> <reaction id="r1" reversible="false"> <listOfReactants> <speciesReference species="S1" stoichiometry="2" sboTerm="SBO:0000010" /> </listOfReactants> <listOfProducts> <speciesReference species="S1" stoichiometry="2" sboTerm="SBO:0000011" /> </listOfProducts> <kineticLaw sboTerm="SBO:0000052"> <math> ... <math> ...</sbml> 26
  • 37. <sbml ...> ... <listOfCompartments> <compartment id="cell" size="1e-15" /> </listOfCompartments> <listOfSpecies> <species compartment="cell" id="S1" initialAmount="1000" /> <species compartment="cell" id="S2" initialAmount="0" /> <listOfSpecies> <listOfParameters> <parameter id="k" value="0.005" sboTerm="SBO:0000339" /> SBO:0000339 <listOfParameters> <listOfReactions> <reaction id="r1" reversible="false"> <listOfReactants> <speciesReference species="S1" stoichiometry="2" sboTerm="SBO:0000010" /> </listOfReactants> <listOfProducts> <speciesReference species="S1" stoichiometry="2" sboTerm="SBO:0000011" /> </listOfProducts> <kineticLaw sboTerm="SBO:0000052"> <math> ... <math> ...</sbml> “forward bimolecular rate constant, continuous case” 26
  • 38. Le Novère et al., Nature Biotech., 23(12), 2005. 27
  • 39. Model Entity element referenced relationship qualifier (optional) MIRIAM cross-references are simple triples { Data type identifier Data item identifier Annotation qualifier } (Required) (Required) (Optional)Format: URI chosen from Syntax & value space Controlled agreed-upon list depends on data type vocabulary term 28
  • 40. “Term #1.1.1.1 (alcohol dehydrogenase) in the Enzyme Commission’s Enzyme Nomenclature database” urn:miriam:ec-code:1.1.1.1 { { URN scheme established Chosen by the creator of the by the MIRIAM project entry in MIRIAM Resources 29
  • 41. MIRIAM Resources provides URI dictionary & resolverhttp://www.ebi.ac.uk/miriam Community-maintained 30
  • 42. MIRIAM Resources provides URI dictionary & resolverhttp://www.ebi.ac.uk/miriam Community-maintained 30
  • 43. SBML defines a syntax for annotations<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> 31
  • 44. SBML defines a syntax for annotations<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> 31
  • 45. SBML defines a syntax for annotations<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> 31
  • 46. Annotations permit inter-database linking 32
  • 47. Annotations permit inter-database linking 32
  • 48. Even more interesting capabilities are possible http://www.semanticsbml.org 33
  • 49. MIRIAM identifiers now in use by many other projectsData resources Application software• BioModels Database (kinetic models) • ARCADIA• PSI Consortium (protein interaction) • BioUML• Reactome (pathways) • COPASI• Pathway Commons (pathways) • libAnnotationSBML • libSBML• SABIO-RK (reaction kinetics) • Saint• Yeast consensus model database • SBML2BioPAX• E-MeP (structural genomics) • SBML2LaTeX • SBMLeditor • semanticSBML • Snazer • SBW • The Virtual Cell 34
  • 50. Model Procedures ResultsRepresentation format SBRML Minimal info ? requirements Semantics— Mathematical Other annotations annotations annotations 35
  • 51. Model Procedures ResultsRepresentation format SBRML Minimal info ? requirements Semantics— Mathematical Other annotations annotations annotations 35
  • 52. <sbml ...> ... <listOfCompartments> <compartment id="cell" size="1e-15" /> </listOfCompartments> <listOfSpecies> ? <species compartment="cell" id="S1" initialAmount="1000" /> <species compartment="cell" id="S2" initialAmount="0" /> <listOfSpecies> <listOfParameters> <parameter id="k" value="0.005" sboTerm="SBO:0000339" /> <listOfParameters> <listOfReactions> <reaction id="r1" reversible="false"> <listOfReactants> <speciesReference species="S1" stoichiometry="2"sboTerm="SBO:0000010" />... SED-ML = Simulation Experiment Description MLApplication-independent formatCaptures procedures, algorithms,parameter values • Steps to go from model to outputlibSedML project developing API library 36
  • 53. Getting closer to the ideal 37
  • 54. People on SBML Team & BioModels Team SBML Team BioModels.net Team Michael Hucka Nicolas Le Novère Sarah Keating Camille LaibeFrank Bergmann Nicolas Rodriguez Lucian Smith Nick JutyNicolas Rodriguez Lukas Endler Linda Taddeo Vijayalakshmi Chelliah Akiya Joukarou Chen Li Akira Funahashi Harish Dharuri Kimberley Begley Lu Li Bruce Shapiro Enuo He Andrew Finney Mélanie Courtot Ben Bornstein Alexander Broicher Ben Kovitz Arnaud Henry Hamid Bolouri Marco Donizelli Herbert Sauro Visionaries Jo Matthews Hiroaki Kitano Maria Schilstra John Doyle 38
  • 55. 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)National Science Foundation (USA)International Joint Research Program of NEDO (Japan)JST ERATO-SORST Program (Japan)Japanese Ministry of AgricultureJapanese Ministry of Educ., Culture, Sports, Science and Tech.BBSRC (UK)DARPA IPTO Bio-SPICE Bio-Computation Program (USA)Air Force Office of Scientific Research (USA)STRI, University of Hertfordshire (UK)Molecular Sciences Institute (USA)Agencies to thank for supporting SBML & BioModels.net 39
  • 56. Where to find out more SBML http://sbml.orgBioModels Database http://biomodels.net/biomodels MIRIAM http://biomodels.net/miriam MIASE http://biomodels.net/miase SED-ML http://biomodels.net/sed-ml SBO http://biomodels.net/sbo KiSAO http://www.ebi.ac.uk/compneur-srv/kisao/ TEDDY http://www.ebi.ac.uk/compneur-srv/teddy/ SBRML http://tinyurl.com/sbrml Thank you for listening! 40