Relations in Biomedical Ontologies

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Relations in Biomedical Ontologies

• Barry Smith
• Department of Philosophy, University at Buffalo
• National Center for Biomedical Ontology
  (http//ncbo.us)

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Two strategies for creating terminologies and
database schemas

• Ad hoc creation by each clinical or research
  communityvs.
• Pre-established reference ontologies upon which
  specific local applications can draw

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We know that high-quality ontologies can help

• in creating better mappings between human and
  model organism phenotypes
• S Zhang, O Bodenreider, Alignment of Multiple
  Ontologies of Anatomy Deriving Indirect Mappings
  from Direct Mappings to a Reference Ontology,
  AMIA 2005

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Advantages of the methodology of shared
coherently defined definitions

• promotes quality assurance (better coding)
• guarantees automatic reasoning across ontologies
  and across data at different granularities
• yields direct connection to temporally indexed
  instance data

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A basic distinction

• type vs. instance
• science text vs. clinical document
• man vs. Michael

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Instances are not represented in an ontology

• For ontology, it is the scientific
  generalizations that are important
• (but instances must still be taken into account)

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A 515287 DC3300 Dust Collector Fan
B 521683 Gilmer Belt
C 521682 Motor Drive Belt

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Ontology Types Instances




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Ontology A Representation of Types




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Ontology A Representation of Types

• Each node of an ontology consists of
• preferred term (aka term)
• term identifier (TUI, aka CUI)
• synonyms
• definition, glosses, comments

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Ontology A Representation of Types
Nodes in an ontology are connected by
relations primarily is_a ( is subtype of) and
part_of designed to support search, reasoning and
annotation
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Motivation To capture reality

• Inferences and decisions we make are based upon
  what we know of reality.
• An ontology is a computable representation of
  biological reality, which is designed to enable a
  computer to reason over the data we collect about
  this reality in (some of) the ways that we do.

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OBO Relation Ontology
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First step

• Alignment of OBO Foundry ontologies through a
  common system of formally defined relations in
  the OBO Relation Ontology
• See Relations in Biomedical Ontologies, Genome
  Biology Apr. 2005

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• Judith Blake
• The use of bio-ontologies ensures consistency
  of data curation, supports extensive data
  integration, and enables robust exchange of
  information between heterogeneous informatics
  systems. ..
• ontologies formally define relationships
  between the concepts.

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"Gene Ontology Tool for the Unification of
Biology"

• an ontology "comprises a set of well-defined
  terms with well-defined relationships"
• (Ashburner et al., 2000, p. 27)

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is_a (sensu UMLS)

• A is_a B def
• A is narrower in meaning than B
• grows out of the heritage of dictionaries
• (which ignore the basic distinction between types
  and instances)

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is_a

• congenital absent nipple is_a nipple
• cancer documentation is_a cancer
• disease prevention is_a disease
• Nazism is_a social science

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is_a (sensu logic)

• A is_a B def
• For all x, if x instance_of A then x instance_of
  B
• cell division is_a biological process
• adult is_a child ???

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Two kinds of entities

• occurrents (processes, events, happenings)
• cell division, ovulation, death
• continuants (objects, qualities, ...)
• cell, ovum, organism, temperature of organism,
  ...

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is_a (for occurrents)

• A is_a B def
• For all x, if x instance_of A then x instance_of
  B
• cell division is_a biological process

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is_a (for continuants)

• A is_a B def
• For all x, t if x instance_of A at t then x
  instance_of B at t
• abnormal cell is_a cell
• adult human is_a human
• but not adult is_a child

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Part_of as a relation between types is more
problematic than is standardly supposed

• heart part_of human being ?
• human heart part_of human being ?
• human being has_part human testis ?
• human testis part_of human being ?

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two kinds of parthood

• between instances
• Marys heart part_of Mary
• this nucleus part_of this cell
• between types
• human heart part_of human
• cell nucleus part_of cell

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Definition of part_of as a relation between types

• A part_of B Def all instances of A are
  instance-level parts of some instance of B
• ALLSOME STRUCTURE

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part_of (for occurrents)

• A part_of B Def
• For all x, if x instance_of A then there is some
  y, y instance_of B and x part_of y
• where part_of is the instance-level part
  relation

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part_of (for continuants)

• A part_of B def.
• For all x, t if x instance_of A at t then there
  is some y, y instance_of B at t and x part_of y
• where part_of is the instance-level part
  relation
• ALL-SOME STRUCTURE

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How to use the OBO Relation Ontology

• Ontologies are representations of types and of
  the relations between types
• The definitions of these relations involve
  reference to times and instances, but these
  references are washed out when we get to the
  assertions (edges) in the ontology
• But curators should still be aware of the
  underlying definitions when formulating such
  assertions

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part_of (for occurrents)

• A part_of B Def
• For all x, if x instance_of A then there is some
  y, y instance_of B and x part_of y
• where part_of is the instance-level part
  relation

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A part_of B, B part_of C ...

• The all-some structure of such definitions allows
• cascading of inferences (true path rule)
• (i) within ontologies
• (ii) between ontologies
• (iii) between ontologies and repositories of
  instance-data

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Strengthened true path rule

• Whichever A you choose, the instance of B of
  which it is a part will be included in some C,
  which will include as part also the A with which
  you began
• The same principle applies to the other relations
  in the OBO-RO
• located_at, transformation_of, derived_from,
  adjacent_to, etc.

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Kinds of relations

• Between types
• is_a, part_of, ...
• Between an instance and a type
• this explosion instance_of the type explosion
• Between instances
• Marys heart part_of Mary

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In every ontology

• some terms and some relations are primitive
  they cannot be defined (on pain of infinite
  regress)
• Examples of primitive relations
• identity
• instantiation
• (instance-level) part_of
• (instance-level) continuous_with

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transformation_of
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transformation_of

• A transformation_of B Def.
• Every instance of A was at some earlier time an
  instance of B
• adult transformation_of child

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tumor development
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derives_from
C1 c1 at t1
C c at t
time
C' c' at t
ovum
zygote derives_from
sperm
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two continuants fuse to form a new continuant
C1 c1 at t1
C c at t
C' c' at t
fusion
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one initial continuant is replaced by two
successor continuants
C1 c1 at t1
C c at t
C2 c2 at t1
fission
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one continuant detaches itself from an initial
continuant, which itself continues to exist
C c at t
c at t1
C1 c1 at t
budding
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one continuant absorbs a second continuant while
itself continuing to exist
c at t1
C c at t
C' c' at t
capture
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A suite of defined relations between types
Foundational is_apart_of
Spatial located_incontained_inadjacent_to
Temporal transformation_ofderives_frompreceded_by
Participation has_participanthas_agent
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To be added to the Relation Ontology

• lacks (between an instance and a type, e.g. this
  fly lacks wings)
• dependent_on (between a dependent entity and its
  carrier or bearer)
• quality_of (between a dependent and an
  independent continuant)
• functioning_of (between a process and an
  independent continuant)

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tumor development
C1
C c at t
c at t1
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The Granularity Gulf

• most existing data-sources are of fixed, single
  granularity
• many (all?) clinical phenomena cross
  granularities

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transformation_of
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Not only relations

• we applied the same methodology to other
  top-level categories in ontology, e.g.
• process
• function
• boundary
• act, observation
• tissue, membrane, sequence

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Advantages of the methodology of enforcing
commonly accepted coherent definitions

• promote quality assurance (better coding)
• guarantee automatic reasoning across ontologies
  and across data at different granularities
• yields direct connection to times and instances
  in EHR

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TLR2MyD88 complex
has_output
TLR2-MyD88 binding
has_disposition
has_participant
TLR2
LTA binding
has_participant
MyD88
regulated_by
preceded_by
has_lower_level_granularity
has_part
process
TLR2-TLR2 ligand binding
has_participant
TIR domain
TIR-TIR binding
TLR-2 signalling pathway
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The methodology of cross-products

• compound terms in Foundry ontologies should be
  post-composed out of simpler terms linked via
  relational expressions from the RO Relation
  Ontology
• Eg composing PATO increased concentration with
  FMA blood and CheBI glucose to represent
  increased blood glucose phenotypes.

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The methodology of cross-products

• enforcing use of RO in linking terms drawn from
  Foundry ontologies serves
• to reduce arbitrariness and ambiguity which
  marks existing approaches to post-composition
• makes the results of post-composition
  algorithmically processable in virtue of the
  logical definitions provided by the RO

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TLR2MyD88 complex
has_output
TLR2-MyD88 binding
has_disposition
has_participant
TLR2
LTA binding
has_participant
MyD88
regulated_by
preceded_by
has_lower_level_granularity
has_part
process
TLR2-TLR2 ligand binding
has_participant
TIR domain
TIR-TIR binding
TLR-2 signalling pathway
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The Granularity Gulf

• most existing data-sources are of fixed, single
  granularity
• many (all?) clinical phenomena cross
  granularities
• Therefore need to reason across time, tracking
  the order of events in time

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GOs three ontologies
biological process
molecular function
dependent
cellular component
independent
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GOs three ontologies
organism-level biological process
cellular process
molecular function
cellular component
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Normalization of Granular Levels
molecular function
cellular process
organism-level biological process
molecule
cellular component
organism
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molecule
cellular component
organism
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molecule
cellular component
organism
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molecular location
cellular location
organism-level location
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The GO is a canonical representation

• The Gene Ontology is a computational
  representation of the ways in which gene products
  normally function in the biological realm
• Nucl. Acids Res. 2006 34.

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everything here is typical
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The Methodology of Annotations

• Scientific curators use experimental observations
  reported in the biomedical literature to link
  gene products with GO terms in annotations.
• The gene annotations taken together yield a
  slowly growing computer-interpretable map of
  biological reality.
• The process of annotating literature also leads
  to improvements and extensions of the ontology,
  which institutes a virtuous cycle of improvement
  in the quality and reach of both future
  annotations and the ontology itself.

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When we annotate the record of an experiment

• we use terms representing types to capture what
  we learn about
• this experiment (instance), performed here and
  now, in this laboratory
• the instances experimented upon
• These instances are typical they are
  representatives of types
• of experiment (described in FuGO)
• of gene product molecules, molecular functions,
  cellular components, biological processes
  (described in GO)

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Experimental records

• document a variety of instances (particular
  real-world examples or cases), ranging from
  instances of gene products (including individual
  molecules) to instances of biochemical processes,
  molecular functions, and cellular locations

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Experimental records

• provide evidence that gene products of given
  types have molecular functions of given types by
  documenting occurrences in the real world that
  involve corresponding instances of functioning.
• They document the existence of real-world
  molecules that have the potential to execute
  (carry out, realize, perform) the types of
  molecular functions that are involved in these
  occurrences.

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• Glossary
• Instance A particular entity in spatio-temporal
  reality.
• Type A general kind instantiated by an
  open-ended totality of instances which share
  certain qualities and propensities in common of
  the sort that can be documented in scientific
  literature

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Glossary

• Gene product instance A molecule that is
  generated by the expression of a DNA sequence and
  which plays some significant role in the biology
  of the organism.
• Gene product type A type of gene product
  instance.

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Glossary

• Biological process instance (aka occurrence) A
  change or complex of changes on the level of
  granularity of the cell or organism, mediated by
  one or more gene products.
• Biological process type A type of biological
  process instance.

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Glossary

• Cellular component instance A part of a cell,
  including cellular structures, macromolecular
  complexes and spatial locations identified in
  relation to the cell
• Cellular component type A type of cellular
  component.

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Glossary

• Molecular function instance The propensity of a
  gene product instance to perform actions, such as
  catalysis or binding, on the molecular level of
  granularity.
• Molecular function type A type of molecular
  function instance.

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Glossary

• Molecular function execution instance (aka
  functioning) A process instance on the
  molecular level of granularity that is the result
  of the action of a gene product instance.
• Molecular function execution type A type of
  molecular function execution instance (aka a
  type of functioning)

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molecular location
cellular locations
organism-level locations
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organism-level physiology
molecular process
cellular physiology
molecular function (GO)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
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organism-level physiology
cellular physiology
molecular process
normal (functionings)
molecular function (GO)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
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pathophysiology (disease)
pathological (malfunctionings)
pathoanatomy (fly, fish, human ...)
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pathophysiology (disease)
organism-level physiology
cellular physiology
molecular process
molecular function (GO)
pathoanatomy (fly, fish, human ...)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy (GO)
anatomy (fly, fish, human...)
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pathophysiology (disease)
organism-level physiology
cellular physiology
molecular process
molecular function (GO)
phenotype
pathoanatomy (fly, fish, human ...)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
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pathophysiology (disease)
organism-level physiology
cellular physiology
molecular process
molecular function (GO)
phenotype
pathoanatomy (fly, fish, human ...)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
investigation (FuGO)
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End