1. 10-Jun-15Anatoly Sorokin Existing Standards in Systems Biology Anatoly Sorokin Computation Systems Biology Group University of Edinburgh

2. Standard 2000-2010 is decade of standards in biology –31 MIBI standard –56 OBO ontologies –About 80 exchange formats Scope of interest Language Controlled vocabulary

3. Standards and Languages CML – description of chemical structure MathML – representation of mathematical formulas PSI – standard description of protein interaction data AnatML – language to describe interaction at organ level GeneOntology – standard and ontology to describe gene function and regulation

4. Standards for Computational System Biology BioPAX – language for database of biological networks exchange SBML – language of biochemical model exchange CellML – language to describe mathematical models SBGN – visual language for biological model description

5. MI standards Reporting guidelines specify the minimum amount of meta data (information) and data required to meet a specific aimmeta data Aim is to provide enough meta data and data to enable the unambiguous reproduction and interpretation of an experiment. Normally informal human readable specifications that inform the development of formal data models (e.g. XML or UML), data exchange formatsXMLUML 10-Jun-15Anatoly Sorokin

6. Exchange format Strict structure to exchange data of model Mainly XML Well defined meta-model, often supported by software API 10-Jun-15Anatoly Sorokin

7. Ontologies “ontology deals with questions concerning what entities exist or can be said to exist, and how such entities can be grouped, related within a hierarchy, and subdivided according to similarities and differences” Wikipediaentitieshierarchy Often used as controlled vocabulary and description support framework GeneOntology 10-Jun-15Anatoly Sorokin

8. BioPAX “Biological PAthway eXchange - A data exchange ontology and format for biological pathway integration, aggregation and inference”

9. BioPAX Goals BioPAX = Biological PAthway eXchange Data exchange format for pathway data Include support for these pathway types: –Metabolic pathways –Signaling pathways –Protein-protein, molecular interactions –Gene regulatory pathways –Genetic interactions Accommodate representations used in existing databases such as BioCyc, BIND, WIT, aMAZE, KEGG, Reactome, etc. PathwayCommons – collection of pathways in BioPAX –http://www.pathwaycommons.org

10. BioPAX BioPAX ontology and format in OWL (XML) Ontology built using GKB Editor and Protégé Semantic mapping still an issue Level 1 represents metabolic pathway data Level 2 adds support for molecular interactions, post-translational modifications, experimental description from PSI-MI model (Backwards compatible) Level 3 adds support for generics, protein states, rearrange reaction representation

11. BioPAX Ontology: Overview

12. BioPAX Ontology: Top Level Pathway –A set of interactions –E.g. Glycolysis, MAPK, Apoptosis Interaction –A set of entities and some relationship between them –E.g. Reaction, Molecular Association, Catalysis Physical Entity –A building block of simple interactions –E.g. Small molecule, Protein, DNA, RNA Entity Pathway Interaction Physical Entity Subclass (is a) Contains (has a)

13. BioPAX Ontology: Interactions Interaction Control Conversion CatalysisBiochemicalReaction ComplexAssembly ModulationTransport TransportWithBiochemicalReaction Physical Interaction

14. BioPAX Ontology: Physical Entities PhysicalEntity ComplexRNA ProteinSmall Molecule DNA

15. BioPAX and other standards BioPAX PSI-MI 2 SBML, CellML Genetic Interactions Molecular Interactions Pro:Pro All:All Interaction Networks Molecular Non-molecular Pro:Pro TF:Gene Genetic Regulatory Pathways Low Detail High Detail Database Exchange Formats Simulation Model Exchange Formats Rate Formulas Metabolic Pathways Low Detail High Detail Biochemical Reactions Small Molecules Low Detail High Detail

16. Simulation-related standards 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Exchange format Ontology implements Makes sense of

17. SBML “The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biochemical reaction networks. SBML is applicable to metabolic networks, cell-signaling pathways, regulatory networks, and many others. ”

18. SBML –Reaction container for rate law –Species reactants, products, or modifiers of reaction –Compartment container for species –Parameter, Rule, Event

19. Characteristics of SBML Many top-level types, little nesting –Units, Compartment, Species, Parameter, Reaction, Rule, Function, Event Non-modular structure –Next SBML ‘Level’ (3) will introduce modularity Emphasis on reactions Some math implicit –Explicit rate equations; implicit integration –Implicit concentration conversion between compartments Compartments are physical containers for species –Spatial dimensions (volume, surface)

20. Structure of SBML

21. Note field of SBase intended to store information for human to read Annotation field of SBase provide a container for software-generated annotations that are not intended to be seen by humans The id field is usually required for most structures and is used to identify a component within the model definition. The name field is optional and provide a human- readable label for the component.

22. 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Data model Ontology implements Makes sense of

23. MIRIAM Model description require extra information –Biological Description of elements of model –Mathematical Definition of math concepts –Referential Author name Paper reference etc. http://www.ebi.ac.uk/compneur-srv/miriam/ 10-Jun-15Anatoly Sorokin

24. Reference correspondence The model must be encoded in a public, standardized, machine- readable format (SBML, CellML, GENESIS...) The model must comply with the standard in which it is encoded! The model must be clearly related to a single reference description. If a model is composed from different parts, there should still be a description of the derived/combined model. The encoded model structure must reflect the biological processes listed in the reference description. The model must be instantiated in a simulation: All quantitative attributes have to be defined, including initial conditions. When instantiated, the model must be able to reproduce all results given in the reference description within an epsilon (algorithms, round-up errors) 10-Jun-15Anatoly Sorokin

25. Attribution annotation The model has to be named. A citation of the reference description must be joined (completecitation, unique identifier, unambigous URL). The citation should permit to identify the authors of the model. The name and contact of model creators must be joined. The date and time of creation and last modification should be specified. An history is useful but not required. The model should be linked to a precise statement about the terms of distribution. MIRIAM does not require “freedom of use” or “no cost”. 10-Jun-15Anatoly Sorokin

26. External resource annotation The annotation must permit to unambiguously relate a piece of knowledge to a model constituent. The referenced information should be described using a triplet {data-type, identifier, qualifier} –The data-type should be written as a Unique Resource Identifier (URI) –The identifier is analysed within the framework of the data-type. –Data-type and Identifier can be combined in a single URI http://www.myResource.org/#myIdentifier urn:lsid:myResource.org:myIdentifier –Qualifiers (optional) should refine the link between the model constitutent and the piece of knowledge: “has a”, “is version of”, “is homolog to” etc. 10-Jun-15Anatoly Sorokin

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28. 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Data model Ontology implements Makes sense of

29. SBO Part of OBO Foundry Assign meanings to mathematical elements of SBML Allows automatic validation of semantic consistency of math part of model http://www.ebi.ac.uk/sbo 10-Jun-15Anatoly Sorokin

30. SBO Types and roles of reaction participants, including terms like “substrate”, “catalyst” etc., but also “macromolecule”, or “channel”. Parameter used in quantitative models. This vocabulary includes terms like “Michaelis constant”, “forward unimolecular rate constant”etc. A term may contain a precise mathematical expression stored as a MathML lambda function. The variables refer to other parameters. Mathematical expressions. Examples of terms are “mass action kinetics”, “Henri-Michaelis-Menten equation” etc. A term may contain a precise mathematical expression stored as a MathML lambda function. The variables refer to the other vocabularies. Modelling framework to precise how to interpret the rate-law. E.g. “continuous modelling”, “discrete modelling” etc. Event type, such as “catalysis” or “addition of a chemical group”. 10-Jun-15Anatoly Sorokin

31. SBO 10-Jun-15Anatoly Sorokin

32. 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Data model Ontology implements Makes sense of

33. MIASE Minimum Information About a Simulation Experiment –What base model to use & which modifications to apply –What simulation task to run on those models (algorithms, see KiSAO; simulation parameters) –How to post-process the numerical results and to present them http://www.ebi.ac.uk/compneur-srv/miase/ Subset of MISE bould be encoded in SED-ML 10-Jun-15Anatoly Sorokin

34. SED-ML Encode MIASE requirements 10-Jun-15Anatoly Sorokin

35. Description of models 10-Jun-15Anatoly Sorokin

36. Description of models 10-Jun-15Anatoly Sorokin

37. Simulations 10-Jun-15Anatoly Sorokin

38. Simulations 10-Jun-15Anatoly Sorokin

39. Simulation task 10-Jun-15Anatoly Sorokin

40. Data generation 10-Jun-15Anatoly Sorokin

41. Data generation 10-Jun-15Anatoly Sorokin

42. Production of results 10-Jun-15Anatoly Sorokin

43. 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Data model Ontology implements Makes sense of

44. KiSAO Kinetic Simulation Algorithm Ontology – Classification of simulation algorithms & methods –Definition, literature references –Relations between different simulation algorithms & methods http://www.ebi.ac.uk/compneur- srv/kisao/index.html 10-Jun-15Anatoly Sorokin

45. KiSAO 10-Jun-15Anatoly Sorokin http://bioportal.bioontology.org/visualize/40844

46. 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Data model Ontology implements Makes sense of

47. SBRML Systems Biology Results Markup Language A new markup language for specifying the results from operations on SBML models http://www.comp-sys-bio.org/tiki- index.php?page=SBRML 10-Jun-15Anatoly Sorokin

48. SBRML 10-Jun-15Anatoly Sorokin

49. SBRML 10-Jun-15Anatoly Sorokin

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53. Dimension example 10-Jun-15Anatoly Sorokin

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55. Dimension example 10-Jun-15Anatoly Sorokin

56. 10-Jun-15Anatoly Sorokin Model Simulation Result ? SED-MLSBRML Minimal Requirements Data model Ontology implements Makes sense of

57. TEDDY The TErminology for the Description of DYnamics (TEDDY) project aims to provide an ontology for dynamical behaviours, observable dynamical phenomena, and control elements of bio- models and biological systems in Systems Biology and Synthetic Biology. http://www.ebi.ac.uk/compneur-srv/teddy/ 10-Jun-15Anatoly Sorokin

58. TEDDY top-level structure Temporal Behaviour (concrete behaviours of a model, more or less the same as trajectories): –Oscillation, Steady State, Fixed Point, Cycle,... Behaviour Characteristic (properties to characterise concrete behaviours): –Period, Amplitude,... Behaviour Diversification (system properties describing the ability of systems to exhibit different behaviours): –Bifurcation, Bi-Stability Functional Motif (structural features of a system necessary for specific function): – Negative Feedback, FFL,... 10-Jun-15Anatoly Sorokin

59. TEDDY 10-Jun-15Anatoly Sorokin

60. Questions 10-Jun-15Anatoly Sorokin