How Ontologies Add Value

BioPAX: Biological Pathway Data Exchange Ontology

Joanne LucianoBioPAX Workgroup (biopax.org)

BioPathways Consortium Liaison (biopathways.org)

3 May 2005KM Pro Forum

Bentley College, Waltham MA, USA

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IntroductionBioPAX = Biopathway Exchange Language

Emerged at ISMB

•conceived at ISMB ’01•born at ISMB ’02 •crawling at ISMB ’03 (Level 0.5)•walking at ISMB ’04 (Level 1.0)•now in the “terrible twos”

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Ontology Intro• Natural language does a poor job at

conveying complex information without ambiguity

• Ontologies provide a means to give concise meanings to pieces of data from a particular domain– Thereby facilitating computational operations on

the data

• Ontologies are becoming increasingly common in the biological community– See http://obo.sourceforge.net/obo.htm

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Ontology: Components• Class hierarchy: chemical protein• Relations & attributes: fields (slots) on the

classes, can be other classes• Constraints: Define allowable values and

connections within an ontology• Objects: instances of classes• Values: occupy slots• Controlled vocabularies (CVs)• BioPAX will use class, attributes, constraints,

values and CVs. Objects are user responsibility

* From Peter Karp, “Ontologies: Definitions, Components, Subtypes”, SRI International, presentation available at http://www.biopax.org

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What is a Pathway?Depends on who you ask!

MetabolicPathways

MolecularInteractionNetworks

SignalingPathways

GeneRegulation

Glycolysis Protein-Protein Apoptosis Lac Operon

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High Throughput Experimental Methods

PubMed

Existing Literature

Microarray

Two-HybridMass

Spectrometry

Genetics

Multiple Pathway Databases

Integration Nightmare!

Protein modifications

Function

Interaction Data

Expression

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So many pathway databases…Each has its own

data model, format, and data access methods

Source: Pathway Resource List (http://cbio.mskcc.org/prl/)

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WITBioCycReactomeaMAZEKEGGBINDDIPHPRDMINTIntActPSI formatCSNDBTRANSPATHTRANSFACPubGeneGeneWays

Research Community Needs

PathwayDatabases

Semantic Aggregation, Integration, Inference(Pedantic Aggravation, Irritation, and Interference)

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Without BioPAX With BioPAX

Common “computable semantic” enables scientific discovery

Over 170 DBs and tools

Database

Application

User

A Common Exchange LanguagePromotes collaboration (big science), accessibility

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Closes Gaps in Pathway Data Space Exchange Language Domain

BioPAX

PSI-MI 2SBML,CellML

GeneticInteractions

Molecular InteractionsPro:Pro All:All

Interaction NetworksMolecular Non-molecularPro:Pro TF:Gene Genetic

Regulatory PathwaysLow Detail High Detail

Database ExchangeFormats

Simulation ModelExchange Formats

RateFormulas

Metabolic PathwaysLow Detail High Detail

Biochemical Reactions

Small MoleculesLow Detail High Detail

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Design Goals• Encapsulation: An entire pathway in

one record• Compatible: Use existing standards

wherever possible• Computable: From file reading to

logical inference• Successful: Buy-in from the research

community

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Technical GoalsInteroperability

– Integration and exchange of pathway data– Interchange through a common (standard)

representation– accommodate existing database

representations– provide a basis for future databases– enables development of tools for searching

and reasoning over the data baseDevelopment of tools and API to facilitate

conversion (libBioPAX)

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Technical Goals (cont’d)Why OWL? Why OWL DL?Expressivity (biology = “complex relationships”) • W3C Standard (use existing standards)

“Semantic Web enabled”• XML based (the exchange language in computing)• Machine Computable

– Facilitate integration of knowledge, data, tool development– Uncover inconsistencies and new knowledge

– OWL DL• Enable full reasoning capability for users

from file reading to logical inference• Complete: all conclusions are guaranteed to be

computed• Decidable: all computations will finish in finite time

(with OWL Lite, short amount of time)

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Social LogisticsGet organized

Make the decision & commitment2 or 3 dedicated individuals to be the contact points

Small core group– Bi-weekly conference calls, bi-monthly F2F– Commitment & resources

• Participants willing and able cover their costs• Outside funding (DOE)

Special interests and needs form subgroup task forces• Core group member(s)• Outside experts

International representation & participation (Outreach & Community Building)

• conferences and mailing lists• follow-up and individual

Collaborate with complementary/competing representations

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Social Logistics (cont’d) How we engendered buy in from the field which

made life much easier

Take things in steps:•Pathway Database vision -> Data Exchange Format as 1st step•Data Exchange Format -> Release in Levels of increasing complexity Level 1 supports Metabolic pathways, Level 2

Early success leads to early adoption, leads to increased probability of overall project success.

Get “buy in” and get involvement -leads to acceptance later•Support the existing databases (BioCYC, WIT, BIND, etc.)

–Got database sources to agree to participate in the development to assure that their DBs will be properly represented

•Got database sources to agree to export in the new format once it is defined

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Social Logistics (cont’d)Get “buy in” (continued) • Community Involvement and Support

Core group (represents voice of community, small, committed)Mailing ListUser community interaction (BioPAX-Boston)Subgroups

• International Meetings and Presentations Tool developers

ModelersUsers (researchers)Ontology developersDatabase providersComplementary representations (SBML, CellML)Like mindsGeneral Community

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Implementation of BioPAX

Designed using GKB Editor and Protégé

BioPAX uses OWL to define the “Schema”

BioPAX Instances to store the data

Technically, an ontology with instance data is a knowledge base

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BioPAX – Ontology

Level 1: Metabolic Pathways

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Creating and Editing

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OWL(schema)

Instances (Individuals)

data

Mapping Pathways to BioPAX

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Mapping Pathways to BioPAX

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Challenges & Bottlenecks

• Scientific– What’s a pathway? Depends on who you ask.

• Technical– Each own syntax & semantics– Immaturity of tools for data integration

• Social / Logistical– Community organization and adoption

• Financial– mostly volunteer of stakeholders– Dept of Energy

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Bridging Chemistry and Molecular Biology

Uniprot:P49841

•Different Views have different semantics: Lenses

• When there is a correspondence between objects, a semantic binding is possible

Apply Correspondence Rule:if ?target.xref.lsid == ?bpx:prot.xref.lsidthen ?target.correspondsTo.?bpx:prot

Source: Eric Neumann

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BioPAX increases collaboration and accessibility to the field and enables 'big science' because it delivers a scalable solution

Capture the complex relationships inherent in Biology

Solves some nasty integration problems

Saves a lot of time and money

Enables Computable Biology

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BioPAX Supporting GroupsGroups • Memorial Sloan-Kettering Cancer Center:

G. Bader, M. Cary, J. Luciano, C. Sander• SRI Bioinformatics Research Group:

P. Karp, S. Paley, J. Pick• University of Colorado Health Sciences

Center: I. Shah• BioPathways Consortium: J. Luciano,

E. Neumann, A. Regev, V. Schachter• Argonne National Laboratory: N. Maltsev,

E. Marland• Samuel Lunenfeld Research Institute:

C. Hogue• Harvard Medical School: E. Brauner,

D. Marks, J. Luciano, A. Regev• NIST: R. Goldberg• Stanford: T. Klein• Columbia: A. Rzhetsky• Dana Farber Cancer Institute: J. Zucker

Collaborating Organizations:

• Proteomics Standards Initiative (PSI)• Systems Biology Markup Language

(SBML)• CellML• Chemical Markup Language (CML)

Databases• BioCyc (www.biocyc.org)• BIND (www.bind.ca)• WIT (wit.mcs.anl.gov/WIT2)• PharmGKB (www.pharmgkb.org)

Grants• Department of Energy (Workshop)

The BioPAX Community

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Thank you!

Questions?