The SOFG Anatomy Entry List SAEL

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The SOFG Anatomy Entry List - SAEL

• Helen Parkinson, EBI
• On behalf of the Standards and Ontologies for
  Functional Genomics SAEL Working Group

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Some History

• SOFG 1 Hinxton 2002, Anatomists had a breakout
  group to discuss integration of Anatomy
  ontologies.
• Outcome website set up listing known anatomy
  resources and view, and intent to integrate
  expressed

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Gratuitous Advertising SOFG2
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SOFG/SAEL Workshop

• David Shotton what if the ontologies are not
  orthogonal?

• In April 2004 an international workshop was held
  in Edinburgh to consider issues raised by the
  SOFG discussion
• Participants representing users of Anatomy
  Ontologies
• ArrayExpress, RAD, GXD, EMAGE
• Participants representing Anatomy Ontologies
• Foundational Model of Anatomy (FMA)
• GALEN, Mouse Adult Anatomy
• Mouse Developmental Anatomy (EMAP)
• Edinburgh Human Developmental Anatomy
• CBIL Controlled Vocabulary for Anatomy

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Integration issues

• Tissues
• Things made of the tissues
• Cells making up the tissues (scale)
• Correspondences Homologies/Orthologies mouse
  tail/C.elegans tail
• Stages
• Developmental derivation
• Relationship types, part-of, is-a, etc and how
  these are used differently
• Considered a specific use case
• The use of anatomy ontologies in the functional
  genomics domain

Slide Alan Rector, Jeremy Rogers
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Functional Genomics Experiments

• Sample-based functional genomics experiments are
  usually limited to what is obtainable by
  conventional dissection
• High level terms are useful
• Detailed ontologies are also useful where
  experimenters need these, for example when laser
  capturing samples
• There are excellent resources already

• Truth Biologists are resistant to data sharing,
  annotation, standardisation, .

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Standard terms are needed for querying
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MGED Ontology

• Supports MIAME, provides terms for annotation of
  experiments (where they do not exist externally)
• Creates a framework to reference external
  ontologies therefore we need external resources
• Requires that external terms be identifiable
• Is implemented in data capture applications
• An anatomy list for this domain needs to be
  simple and be flexible
• Annotation needs are diverse
• Multiple resources can be confusing

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A multiplicity of resources

• Many resources, formats, philosophies, purposes,
  variable content,

• Compare the FMA vs. the adult mouse

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Anatomy Terminologies and Ontologies
Slide Cornelius Rosse
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Foundational Model of Anatomy (FMA)

• FMA uses a frame-based formalism
• concerned with the representation of concepts and
  relationships in a form that is understandable to
  humans and machine readable
• Human/vertebrate
• Definition structural attributes
• Content organism to biological macromolecule
• Serves as a reference ontology

Slide Cornelius Rosse
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FM Explorer
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Adult Mouse _at_ Jax Vocab browser

• Anatomical structures are organized spatially and
  functionally, using 'is a' and 'part of'
  relationships
• For TS28
• Purpose, encoding and integration of mouse gene
  expression data

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SAEL ..

• is a simple list of 120 terms
• is for low-resolution descriptions of sample
  origin
• terms have ids SAEL1
• contains vertebrate terms at present
• is NOT a new anatomy ontology
• does NOT have defined relationship types
• terms do not have definitions
• is a first step to considering the relationships
  between the SAEL source ontologies
• is NOT intended to replace deeper integration
  efforts

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The SAEL current version 1.0

• Download from www.sofg.org/sael/index.html
• In plain text/OBO format
• Will be maintained by MGED Ontology working gp
  Terry Hayamizu (Jax)
• Suggestions through MGED Ontology sourceforge
  tracker
• Report on the workshop is available
• Review publication from this workshop in CFG

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Testing the content

• SAEL maps to 80 of current terms tested
• So far been tested vs. current annotation in
• ArrayExpress/MIAMExpress OrganismPart 82 terms
• HGMP microarray mouse and human only 97 terms
• SMD - free text microarray sample annotations 22
  terms
• GXD - 80 for blot and cDNA data only
• RAD microarray, uses CBIL

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Implementation

• MIAMExpress ArrayExpress data capture tool uses
  SAEL
• Data in ArrayExpress will be mapped to SAEL
• Future submissions will use SAEL
• We will encourage users of the MGED ontology to
  use SAEL where appropriate

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COBrA
XSPAN demo takes place on Wednesday, August 4th
at 11.30am in room Alsh 2 Albert Burger
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Mapping source ontologies to SAEL

• Adult mouse anatomy, FMA mapped to date
• Mouse Developmental, GALEN, CBIL others to do
• Using COBrA from the XSPAN project -
  www.xspan.org
• Allows manual mapping between ontologies
• Creates an OWL format mapping file
• Reads DAGEdit flat file format, GO XML/RDF, GO
  RDFS and OWL
• Mappings available from www.sofg.org

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Web services

• A WSDL has been defined for SAEL
• dev_stage, is_tissue, is_cell_type, is_organ,
  is_system, superclass, subclass, part, part_of,
  uri, definition, authority, history, name,
  synonym
• Source ontologies will provide a web service
  supporting queries and returning the attribute
  list
• WSDL has been tested vs. Adult mouse anatomy, FMA
  and developmental mouse anatomy, will be tested
  further

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Proposed web services architecture

• SAEL and will be made available via user
  interface and programmatically
• Querying multiple ontologies will be supported by
  the central SAEL web service
• The SAEL Portal provides a graphical user
  interface for researchers to look up the mappings
  between the SAEL list of anatomical entities and
  the target ontologies.
• Will be implemented in 2 phases, SAEL portal
  first, then local ws

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Future

• We welcome collaboration and mapping of other
  relevant ontologies proceeds e.g. EVOC
• Building web services architecture, XSPAN
• Refining SAEL, completing mapping
• Inclusion in MGED Extended ontology (v1.2)
• Deeper integration of anatomy ontologies
• Decisions on handling of null mappings
• Modification of relationship types in current
  version
• Protégé version from Alan Rector

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Acknowledgements

• SAEL workshop participants Stuart Aitken, Albert
  Burger, Richard Baldock, Jonathan Bard, Duncan
  Davidson, Terry Hayamizu, Helen Parkinson, Alan
  Rector, Jeremy Rogers, Martin Ringwald, Cornelius
  Rosse, Chris Stoeckert
• John Gennari
• Niran Abeygunawardena, EBI Website, MIAMExpress
  implementation
• Funders MRC-HGU, MGED, EU TEMBLOR
• Jeremy Gollub -SMD, Naran Hirani/Tom Freeman
  HGMP

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Gratuitous Advertising SOFG2
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Bio-Ontologies Panel Discussion

• Michael Ashburner, Dept of Genetics Univeristy of
  Cambridge
• Crispin Miller, Bioinformatics and
  Onco-informatics Group
• Jeremy Rogers, Medical Informatics Group,
  University of Manchester
• Barry Smith, Institute for Formal Ontology and
  Medical Information Science, University of
  Leipzig and Buffalo, State University of NY

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SWOT analysis

• 131,000 hits on Google

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SWOT 2

• Strengths
• Weaknesses
• Orientated towards the internal aspects of
  bio-ontologies or an individual ontology
• Opportunities
• Threats
• Those factors external to bio-ontologies or an
  individual ontology

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Panel Perspective

• Michael Ashburner
• Pragmatic ontologies for real utility in biology
  
• Jeremy Rogers
• Pragmatic economic or user-led development risks
  the lowest common denominator or the mediocre
  the Trabant or the Ford Mondeo. Theory-led
  development may ignore practicality and expense
  the Formula One race car. How can such extremes
  be avoided in ontology engineering ?
• Crispin Miller
• There is generally a difference between what we
  would like to say, and what our computers are
  capable of interpreting. How do we build
  ontology-based systems that can successfully
  resolve the tensions arising from this
• Barry Smith
• Physics has pure mathematics as its formal
  backbone. What is the counterpart of pure
  mathematics in biology? Answer formal ontology.

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Criteria for future chairs

• combination of School Mistress sternness,
  eloquence, and opinionation Phil Lord
• ability to pick people out of the audience
  Robert Stevens

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Michael

• GO
• Strengthswide uptake, community project,
  designed for a single problem gene product
  attributes, dev of ontol pragmatic (weakness?),
  open, to sw
• Weakness Pragmatic design and build, qc
  mechanism, and implementation issues in DB, lack
  of formalism, no idea would be universal
• Opp. - world domination, achieving greater
  integration across species
• Threats long term stability academia, funding
  models, diversion into philoso

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Crispin

• S - structure info
• W -
• O abstraction level problematic
• T - Knowing where to stop, ontology is linked to
  tools, cultural issues,

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Jeremy

• Strengths community of eager users scope,
  where to start
• Open source
• T semantic web hype, succession of curators

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Helen

• S collaboration
• W legacy data management, costs, maintenance,
  user uptake
• O improved data retrieval, query,
  formalisation,
• T reinvention of the wheel

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Barry Smith

• MA completion/failure
• S exists
• O data, make it interoperable
• W pragmatic decisions become entrenched,
• T fools paradise OWL is not expressive enough
  
• expressive power cheating is-a overloading,
  need a top level of ontology philosophical qu.
  way that instance is used
• Ontology reality knowledge describing
  knowledge, - assay ontology ? Ontology of
  scientific expts
• Perfection is the enemy of the good !
• Solution more precison