biological ontologies
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Biological Ontologies. Neocles Leontis April 20, 2005. What Is An Ontology?. An ontology is an explicit description of a domain of knowledge: Concepts -- Entities and Relations Properties and attributes of Entities and Relations Constraints on properties and attributes - PowerPoint PPT PresentationTRANSCRIPT
Biological Ontologies
Neocles LeontisApril 20, 2005
What Is An Ontology?• An ontology is an explicit description of a
domain of knowledge:– Concepts -- Entities and Relations– Properties and attributes of Entities and Relations– Constraints on properties and attributes– Individuals (“Instances”)
• An ontology defines: – a common vocabulary– a shared understanding of the domain of knowledge– Commitments on how to use the vocabulary
What Is “Ontology Engineering”?Ontology Engineering: Defining terms in
the domain and relations among them– Defining concepts in the domain (Classes)– Arranging the concepts in a hierarchy
(Subclass-Superclass hierarchy)– Defining which attributes and Properties
classes can have (slots) and constraints on their values (facets)
– Defining individuals and filling in slot values (instantiation)
Why Develop an Ontology?
• To share common understanding of the structure of information – among people– among software agents
• To enable reuse of domain knowledge– to avoid “re-inventing the wheel”– to introduce standards to allow
interoperability between ontologies
More Reasons…• To make domain assumptions
explicit– easier to change domain assumptions– easier to understand and update
legacy data• To separate domain knowledge
from the operational knowledge– re-use domain and operational
knowledge separately
An Ontology Is Often Just the Beginning
Ontologies
Problem-solving
methods
DatabasesDeclarestructure
Knowledgebases
Providedomain
description
Ontology-Development Process
In Logical order:determine
scopeconsider
reuseenumerate
termsdefine
classesdefine
propertiesdefine
constraintscreate
instances
In reality - an iterative process:determine
scopeconsider
reuseenumerate
termsdefine
classesconsider
reuseenumerate
termsdefine
classes
defineproperties
createinstances
defineclasses
defineproperties
defineconstraints
createinstances
defineclasses
considerreuse
defineproperties
defineconstraints
createinstances
Protégé• Graphical ontology-development
tool• Supports a rich knowledge mode• Open-source and freely available
(http://protege.stanford.edu)
Authoring Program (Protégé 2000)• Enforces the implementation of foundational
principles and definitional desiderata• Frame-based architecture compatible with OKBC
protocol = Open Knowledge Base Connectivity• Frames are used to represent anatomical
concepts• Frames allow for distinguishing between class
and instance• Protégé allows for selective inheritance of
attributes• Protégé enhances specificity and expressivity of
attributes by assigning them their own attributes.
Determine Domain and Scope
• What is the domain that the ontology will cover?
• Who is going to use the ontology?• For what are they (we) going to use the
ontology?• For what types of questions should the
information in the ontology provide answers (competency questions)?
Answers to these questions may change during the lifecycle
determinescope
considerreuse
enumerateterms
defineclasses
defineproperties
defineconstraints
createinstances
RNA Ontology Scope: DOMAIN
– RNA Sequences (1D) -- Coding and Non-Coding
– RNA 2D structures – RNA 3D structures– Alignments of homologous RNA sequences– Relationships between alignments and 3D
structures
RNA Ontology ScopeWHO?
– Molecular biologists & biochemists – Structural biologists – Evolutionary biologists– Nanotechnologists
RNA Ontology Scope: WHAT?
– How to improve prediction of RNA 3D structure
– How to improve sequence alignments of homologous RNAs
– To identify and annotate RNA genes in genomes
– How are RNA 3D structure and evolution coupled?
– How is RNA evolution coupled to biological evolution
Consider Reuse
• Why reuse other ontologies?– to save the effort– to interact with the tools that use
other ontologies– to use ontologies that have been
validated through use in applications
determinescope
considerreuse
enumerateterms
defineclasses
defineproperties
defineconstraints
createinstances
Enumerate Important Terms
• What are the terms (entities) we need to talk about?
• What are the properties and attributes of these entities?
• What are the relationships between entities?
considerreuse
determinescope
enumerateterms
defineclasses
defineproperties
defineconstraints
createinstances
Define Classes and the Class Hierarchy
• A class is a concept in the domain– a class of wines– a class of wineries– a class of red wines
• A class is a collection of elements with similar properties
• Instances of classes– a glass of California wine you’ll have for lunch
considerreuse
determinescope
defineclasses
defineproperties
defineconstraints
createinstances
enumerateterms
Class Hierarchy
Class Inheritance• Classes usually constitute a taxonomic
hierarchy (a subclass-superclass hierarchy)• A class hierarchy is usually an IS-A hierarchy:
an instance of a subclass is an instance of a superclass
• If you think of a class as a set of elements, a subclass is a subset
FMA -- High Level Scheme• FMA = (AT, ASA, ATA, Mk)
– AT = Anatomy taxonomy (assigns anatomical entities as class concepts
– ASA = Anatomy Structural Abstraction -- includes structural relationships among entities of the AT
– ATA = Anatomical Transformation Abstraction -- relationships that describe morphological & physical transformations of anatomical entities
– MK = Metaknowledge -- principles and sets of rules
ASA -- High Level Scheme• ASA = (Dt, PPt, Bn, Pn, SAn)
– Dt = Dimensional taxonomy– PPt = Physical Properties taxonomy– Bn = Boundary network– Pn = Partonomy network– SAn = Spatial Association network
Boundary Network (Bn)• Specification of boundaries is critical for
segmentation of images and volumetric datasets
• Definition: Boundary = Non-material physical anatomical entity of two or fewer dimensions that delimits anatomical entities that are of one higher dimension than the bounding entity
Boundary Network (Bn)Inverse Relationships:
-bounded by--bounds-
Real vs. Virtual Boundaries:Rea boundaries correspond to its surface and designate discontinuities between constitutional parts of anatomical entities
Partonomy Network (Pn)Inverse Relationships:
-has part-
Rule of Dimensional Consistency
Distinguishes between boundary and partonomy relationships.
Parthood relations -- only allowed for entities of the same dimension
Ex: Cavity of stomach (3D) -has part- Cavity of pyloric antrum (3D)
Ex: Internal surface of stomach (2D) -has part- Internal surface of pyloric antrum (2D)
What to Reuse?• Ontology libraries
– DAML ontology library (www.daml.org/ontologies)
– Ontolingua ontology library (www.ksl.stanford.edu/software/ontolingua/)
– Protégé ontology library (protege.stanford.edu/plugins.html)
• Upper ontologies– IEEE Standard Upper Ontology
(suo.ieee.org)– Cyc (www.cyc.com)
RNA Ontology Consortium• To share common understanding of the
structure of information – among people– among software agents
• To enable reuse of domain knowledge– to avoid “re-inventing the wheel”– to introduce standards to allow
interoperability
What to Reuse? (II)• General ontologies
– DMOZ (www.dmoz.org)– WordNet (www.cogsci.princeton.edu/~wn/)
• Domain-specific ontologies– UMLS Semantic Net– GO (Gene Ontology) (www.geneontology.org
)– FMA (Foundational Model of Anatomy)
Foundational Model of Anatomy
QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.
http://sig.biostr.washington.edu/projects/fm/index.html
• Reference ontology for biomedical informatics
• Representation of Anatomical Entities and Relationships
• Symbolic modeling of the structure of the human body at the highest level of granularity
• Evolving Resource for knowledge-based applications requiring anatomical information
FMA: Modeling Challenges• Representing complex structural relations• Representing different levels of granularity• Developing a model that is scalable to a
very large number of concepts• Using consistent organizational principles