bioinformatics – a glimpse of the future生物信息学的未来

8-Jan-18,Anatoly Sorokin,Existing Standards in Systems Biology,Anatoly Sorokin Computation Systems Biology GroupUniversity of Edinburgh,Standard,2000-2010 is decade of standards in biology31 MIBI standard56 OBO ontologiesAbout 80 exchange formatsScope of interestLanguage Controlled vocabulary,Standards and Languages,CML description of chemical structureMathML representation of mathematical formulasPSI standard description of protein interaction dataAnatML language to describe interaction at organ levelGeneOntology standard and ontology to describe gene function and regulation,Standards for Computational System Biology,BioPAX language for database of biological networks exchangeSBML language of biochemical model exchangeCellML language to describe mathematical models SBGN visual language for biological model description,MI standards,Reporting guidelines specify the minimum amount of meta data (information) and data required to meet a specific aim 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 formats,8-Jan-18,Anatoly Sorokin,Exchange format,Strict structure to exchange data of modelMainly XML Well defined meta-model, often supported by software API,8-Jan-18,Anatoly Sorokin,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” WikipediaOften used as controlled vocabulary and description support frameworkGeneOntology,8-Jan-18,Anatoly Sorokin,BioPAX,“Biological PAthway eXchange - A data exchange ontology and format for biological pathway integration, aggregation and inference”,BioPAX Goals,BioPAX = Biological PAthway eXchangeData exchange format for pathway dataInclude support for these pathway types:Metabolic pathwaysSignaling pathwaysProtein-protein, molecular interactionsGene regulatory pathwaysGenetic interactionsAccommodate representations used in existing databases such as BioCyc, BIND, WIT, aMAZE, KEGG, Reactome, etc.PathwayCommons collection of pathways in BioPAX,BioPAX,BioPAX ontology and format in OWL (XML)Ontology built using GKB Editor and ProtgSemantic mapping still an issueLevel 1 represents metabolic pathway dataLevel 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,BioPAX Ontology: Overview,BioPAX Ontology: Top Level,PathwayA set of interactionsE.g. Glycolysis, MAPK, ApoptosisInteractionA set of entities and some relationship between themE.g. Reaction, Molecular Association, CatalysisPhysical EntityA building block of simple interactionsE.g. Small molecule, Protein, DNA, RNA,BioPAX Ontology: Interactions,Interaction,Control,Conversion,Catalysis,BiochemicalReaction,ComplexAssembly,Modulation,Transport,TransportWithBiochemicalReaction,Physical Interaction,BioPAX Ontology: Physical Entities,PhysicalEntity,Complex,RNA,Protein,Small Molecule,DNA,BioPAX and other standards,BioPAX,PSI-MI 2,SBML,CellML,GeneticInteractions,Database ExchangeFormats,Simulation ModelExchange Formats,RateFormulas,Biochemical Reactions,Simulation-related standards,8-Jan-18,Anatoly Sorokin,MinimalRequirements,Exchange format,Ontology,implements,implements,Makes sense of,Makes sense of,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. ”,SBML,Reactioncontainer for rate lawSpeciesreactants, products, or modifiers of reactionCompartmentcontainer for speciesParameter, Rule, Event,Characteristics of SBML,Many top-level types, little nestingUnits, Compartment, Species, Parameter, Reaction, Rule, Function, EventNon-modular structureNext SBML Level (3) will introduce modularityEmphasis on reactionsSome math implicitExplicit rate equations; implicit integrationImplicit concentration conversion between compartmentsCompartments are physical containers for speciesSpatial dimensions (volume, surface),Structure of SBML,Structure of SBML,Note field of SBase intended to store information for human to readAnnotation field of SBase provide a container for software-generated annotations that are not intended to be seen by humansThe 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.,8-Jan-18,Anatoly Sorokin,MinimalRequirements,Data model,Ontology,implements,implements,Makes sense of,Makes sense of,MIRIAM,Model description require extra informationBiologicalDescription of elements of modelMathematicalDefinition of math conceptsReferentialAuthor namePaper reference etc. http:/www.ebi.ac.uk/compneur-srv/miriam/,8-Jan-18,Anatoly Sorokin,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),8-Jan-18,Anatoly Sorokin,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”.,8-Jan-18,Anatoly Sorokin,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.myR/#myIdentifier urn:lsid:myR: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.,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,MinimalRequirements,Data model,Ontology,implements,implements,Makes sense of,Makes sense of,SBO,Part of OBO FoundryAssign meanings to mathematical elements of SBMLAllows automatic validation of semantic consistency of math part of modelhttp:/www.ebi.ac.uk/sbo,8-Jan-18,Anatoly Sorokin,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”.,8-Jan-18,Anatoly Sorokin,SBO,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,MinimalRequirements,Data model,Ontology,implements,implements,Makes sense of,Makes sense of,MIASE,Minimum Information About a Simulation ExperimentWhat base model to use 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,8-Jan-18,Anatoly Sorokin,SED-ML,Encode MIASE requirements,8-Jan-18,Anatoly Sorokin,Description of models,8-Jan-18,Anatoly Sorokin,Description of models,8-Jan-18,Anatoly Sorokin,Simulations,8-Jan-18,Anatoly Sorokin,Simulations,8-Jan-18,Anatoly Sorokin,Simulation task,8-Jan-18,Anatoly Sorokin,Data generation,8-Jan-18,Anatoly Sorokin,Data generation,8-Jan-18,Anatoly Sorokin,Production of results,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,MinimalRequirements,Data model,Ontology,implements,implements,Makes sense of,Makes sense of,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,8-Jan-18,Anatoly Sorokin,KiSAO,8-Jan-18,Anatoly Sorokin,/visualize/40844,8-Jan-18,Anatoly Sorokin,MinimalRequirements,Data model,Ontology,implements,implements,Makes sense of,Makes sense of,SBRML,Systems Biology Results Markup LanguageA new markup language for specifying the results from operations on SBML models/tiki-index.php?page=SBRML,8-Jan-18,Anatoly Sorokin,SBRML,8-Jan-18,Anatoly Sorokin,SBRML,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,8-Jan-18,Anatoly Sorokin,Dimension example,8-Jan-