April 10, 2007

Principles for BuildingBiomedical Ontologies

ISMB 2005

April 10, 2007

Ontology (as a branch ofphilosophy)

The science of what is:of the kinds and structures of the objects, andtheir properties and relations in every area ofreality.

In simple terms, it seeks the classification ofentities.

Defined by a scientific field's vocabulary andby the canonical formulations of its theories.

Seeks to solve problems which arise in thesedomains.

April 10, 2007

In computer science, there is aninformation handling problem

Different groups of data-gatherers developtheir own idiosyncratic terms and concepts ofwhich they represent information.

To put this information together, methodsmust be found to resolve terminological andconceptual incompatibilities.

Again, and again, and again…

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The Solution to this Tower of Babelproblem

A shared, common, backbone taxonomy ofrelevant entities, and the relationshipsbetween them within an application domain

This is referred to by information scientists asan ’Ontology'.

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Which means…Instances are not included!

It is the generalizations that areimportant

Please keep this in mind, it is crucial tounderstanding the tutorial

April 10, 2007

Principles for BuildingBiomedical Ontologies

Barry Smithhttp://ifomis.de

April 10, 2007

Ontologies as ControlledVocabularies

expressing discoveries in the lifesciences in a uniform way

providing a uniform framework formanaging annotation data deriving fromdifferent sources and with varying typesand degrees of evidence

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Overview Following basic rules helps make better

ontologies We will work through the principles-

based treatment of relations inontologies, to show how ontologies canbecome more reliable and morepowerful

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Why do we need rules for goodontology?

Ontologies must be intelligible both tohumans (for annotation) and to machines (forreasoning and error-checking)

Unintuitive rules for classification lead to entryerrors (problematic links)

Facilitate training of curators Overcome obstacles to alignment with other

ontology and terminology systems Enhance harvesting of content through

automatic reasoning systems

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First Rule: Univocity

Terms (including those describingrelations) should have the samemeanings on every occasion of use.

In other words, they should refer to thesame kinds of entities in reality

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Example of univocity problemin case of part_of relation

(Old) Gene Ontology: ‘part_of’ = ‘may be part of’

flagellum part_of cell ‘part_of’ = ‘is at times part of’

replication fork part_of the nucleoplasm ‘part_of’ = ‘is included as a sub-list in’

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Second Rule: Positivity

Complements of classes are notthemselves classes.

Terms such as ‘non-mammal’ or ‘non-membrane’ do not designate genuineclasses.

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Third Rule: Objectivity

Which classes exist is not a function ofour biological knowledge.

Terms such as ‘unknown’ or‘unclassified’ or ‘unlocalized’ do notdesignate biological natural kinds.

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Fourth Rule: Single Inheritance

No class in a classificatoryhierarchy should have more thanone is_a parent on the immediatehigher level

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Rule of Single Inheritance

no diamonds:

Cis_a2

Bis_a1

A

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Problems with multiple inheritance

B C

is_a1 is_a2

A

‘is_a’ no longer univocal

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‘is_a’ is pressed into service to meana variety of different things

shortfalls from single inheritance are oftenclues to incorrect entry of terms andrelations

the resulting ambiguities make the rulesfor correct entry difficult to communicate tohuman curators

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is_a Overloading

serves as obstacle to integration withneighboring ontologies

The success of ontology alignmentdepends crucially on the degree towhich basic ontological relations suchas is_a and part_of can be relied on ashaving the same meanings in thedifferent ontologies to be aligned.

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Use of multiple inheritance

The resultant mélange makes coherentintegration across ontologies achievable (atbest) only under the guidance of humanbeings with relevant biological knowledge

How much should reasoning systems beforced to rely on human guidance?

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Fifth Rule: Intelligibility ofDefinitions

The terms used in a definition should besimpler (more intelligible) than the termto be defined

otherwise the definition provides noassistance to human understanding for machine processing

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To the degree that the aboverules are not satisfied, errorchecking and ontologyalignment will be achievable,at best, only with humanintervention and via bruteforce

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Some rules are Rules of Thumb The world of biomedical research is a world of difficult

trade-offs The benefits of formal (logical and ontological) rigor

need to be balanced Against the constraints of computer tractability, Against the needs of biomedical practitioners.

BUT alignment and integration of biomedicalinformation resources will be achieved only to thedegree that such resources conform to thesestandard principles of classification and definition

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Definitions should be intelligibleto both machines and humans

Machines can cope with the full formalrepresentation

Humans need to use modularity Plasma membrane

is a cell part [immediate parent]

that surrounds the cytoplasm [differentia]

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Terms and relations should haveclear definitions

These tell us how the ontology relatesto the world of biological instances,meaning the actual particulars in reality: actual cells, actual portions of cytoplasm,

and so on…

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Sixth Rule: Basis in Reality

When building or maintaining anontology, always think carefully at howclasses (types, kinds, species) relate toinstances in reality

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Axioms governing instances

Every class has at least one instance

Every genus (parent class) has aninstantiated species (differentia + genus)

Each species (child class) has a smaller classof instances than its genus (parent class)

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Axioms governing Instances

Distinct classes on the same level nevershare instances

Distinct leaf classes within aclassification never share instances

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siamese

mammal

cat

organism

substancespecies,genera

animal

instances

frogleaf class

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Interoperability

Ontologies should work together ways should be found to avoid redundancy

in ontology building and to support reuse ontologies should be capable of being used

by other ontologies (cumulation)

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Main obstacle to integration

Current ontologies do not deal well with Time and Space and Instances (particulars)

Our definitions should link the terms inthe ontology to instances in spatio-temporal reality

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Benefits of well-definedrelationships

If the relations in an ontology are well-defined, then reasoning can cascade fromone relational assertion (A R1 B) to the next(B R2 C). Relations used in ontologies thusfar have not been well defined in this sense.

Find all DNA binding proteins should also findall transcription factor proteins because Transcription factor is_a DNA binding protein

April 10, 2007

How to define A is_a B

A is_a B =def.

1. A and B are names of universals(natural kinds, types) in reality

2. all instances of A are as a matter ofbiological science also instances of B

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Biomedical ontologyintegration / interoperability

Will never be achieved through integration ofmeanings or concepts

The problem is precisely that different usercommunities use different concepts

What’s really needed is to have well-defined commonly used relationships

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Idea:

Move from associative relationsbetween meanings to strictly definedrelations between the entitiesthemselves.

The relations can then be usedcomputationally in the way required

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Key idea:To define ontological relations For example: part_of, develops_from Definitions will enable computation It is not enough to look just at classes or

types. We need also to take account of instances

and time

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Kinds of relations

Between classes: is_a, part_of, ...

Between an instance and a class this explosion instance_of the class

explosion Between instances:

Mary’s heart part_of Mary

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Seventh Rule: DistinguishUniversals and Instances

A good ontology must distinguishclearly between universals (types, kinds, classes)and instances (tokens, individuals,

particulars)

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Don’t forget instances whendefining relations

part_of as a relation between classesversus part_of as a relation betweeninstances

nucleus part_of cell your heart part_of you

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Part_of as a relation betweenclasses is more problematicthan is standardly supposed

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

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Why distinguish universals frominstances?

What holds on the level of instances may not hold onthe level of universals

nucleus adjacent_to cytoplasm Not: cytoplasm adjacent_to nucleus seminal vesicle adjacent_to urinary bladder Not: urinary bladder adjacent_to seminal vesicle

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part_of

part_of must be time-indexed for spatialuniversals

A part_of B is defined as:Given any instance a and any time t,If a is an instance of the universal A at t,then there is some instance b of the universal Bsuch thata is an instance-level part_of b at t

April 10, 2007

Principles for BuildingBiomedical Ontologies:A GO

PerspectiveDavid Hill

Mouse Genome InformaticsThe Jackson Laoratory

April 10, 2007

How has GO dealt with some specificaspects of ontology development? Univocity Positivity Objectivity Single Inheritance Definitions

Formal definitions Written definitions

Basis in Reality Universals &

Instances Ontology

Alignment

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Tactile senseTactionTactition

?

The Challenge of Univocity:People call the same thing by different names

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Tactile senseTactionTactition

perception of touch ; GO:0050975

Univocity: GO uses 1 term and manycharacterized synonyms

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= bud initiation

= bud initiation

= bud initiation

The Challenge of Univocity: People use thesame words to describe different things

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Bud initiation? How isa computer to know?

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= bud initiation sensu Metazoa

= bud initiation sensu Saccharomyces

= bud initiation sensu Viridiplantae

Univocity: GO adds “sensu” descriptors todiscriminate among organisms

April 10, 2007

The Importance of synonyms for utility:How do we represent the function of tRNA?

Biologically, what does the tRNA do?Identifies the codon and inserts the aminoacid in the growing polypeptide

Molecular_function

Triplet_codon amino acid adaptor activity

GO Definition: Mediates the insertion of an amino acid at the correctpoint in the sequence of a nascent polypeptide chain during proteinsynthesis.

Synonym: tRNA

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But Univocity is also Dependenton a User’s Perspective

Development (The biological process whose specificoutcome is the progression of an organism over timefrom an initial condition to a later condition)

--part_of hepatocyte differentiation

----part_of hepatocyte fate commitment

------part_of hepatocyte fate specification

------part_of hepatocyte fate determination

----part_of hepatocyte development

April 10, 2007

But Univocity is also Dependenton a User’s Perspective

So from the perspective of GO a hepatocyte beginsdevelopment after it is committed to its fate. Its initialcondition is after cell fate commitment.

But! A User may ask show me things that have to do withhepatocyte development.

Do they mean show me things that have to dowith ‘hepatocyte development” or do they meanshow me things that have to do with‘development’ and a ‘hepatocyte’?

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The Challenge of Positivity

Some organelles are membrane-bound.A centrosome is not a membrane bound organelle,but it still may be considered an organelle.

April 10, 2007

The Challenge of Positivity: Sometimesabsence is a distinction in a Biologist’s mind

non-membrane-bound organelle GO:0043228

membrane-bound organelleGO:0043227

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Positivity

Note the logical difference between “non-membrane-bound organelle” and “not a membrane-bound organelle”

The latter includes everything that is nota membrane bound organelle!

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The Challenge of Objectivity: Databaseusers want to know if we don’t know

anything (Exhaustiveness with respect toknowledge)

We don’t know anything about a gene product with

respect to these

We don’t know anything about the ligand that

binds this type of GPCR

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Objectivity

How can we use GO to annotate geneproducts when we know that we don’t haveany information about them? Currently GO has terms in each ontology to

describe unknown An alternative might be to annotate genes to root

nodes and use an evidence code to describe thatwe have no data.

Similar strategies could be used for things likereceptors where the ligand is unknown.

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GPCRs with unknown ligands

We couldannotate to

this

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Single Inheritance

GO has a lot of is_a diamonds Some are due to

incompleteness/inaccuracies within thegraph

Some are due to a mixture of dissimilarentities within the graph at the same level

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Is_a diamond in GO Processbehavior

locomotory behavior larval behavior

larval locomotory behavior

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Is_a diamond in GO Functionenzyme regulator

activity

GTPase regulatoractivity

enzyme activatoractivity

GTPase activatoracivity

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Is_a diamond in GO CellularComponent

organelle

non-membrane boundorganelle

intracellularorganelle

non-membrane boundintracellular organelle

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Technically the diamonds arecorrect, but could be eliminated

locomotory behavior larval behavior

GTPase regulatoractivity

enzyme activatoractivity

non-membrane boundorganelle

intracellularorganelle

What do these pairs have in common?

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What do the middle pair of termsall have in common?

locomotory behavior larval behavior

GTPase regulatoractivity

enzyme activatoractivity

non-membrane boundorganelle

intracellularorganelle

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They are all differentiated from theparent term by a different factor

locomotory behavior larval behavior

GTPase regulatoractivity

enzyme activatoractivity

non-membrane boundorganelle

intracellularorganelle

Type of behavior vs. what is behaving

What is regulated vs. type of regulator

Type of organelle vs. location of organelle

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Insert an intermediate grouping termbehavior

locomotory behavior larval behavior

larval locomotory behavior

behavior of a thing

descriptive behavior These actually

describe two differentrelationships

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Create a new relationship typebehavior

locomotory behavior larval behavior

larval locomotory behavior

behavior of a thing

descriptive behavior

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Why insert terms that no one woulduse?behavior

locomotory behavior larval behavior rhythmic behavior adult behavior

By the structure of this graph, locomotory behaviorhas the same relationship to larval behavior

as to rhythmic behavior

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Why insert terms (types) that no onewould use?

behavior

locomotory behavior larval behaviorrhythmic behavior adult behavior

But actually, locomotory behavior/rhythmic behaviorand larval behavior/adult behavior group naturally

Descriptivebehavior

Behaviorof athing

This type of single step differentiation of types between levels would allow us to use distancesbetween nodes and levels to compare similarity.

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GO DefinitionsA definition written by

a biologist:necessary & sufficient

conditionswritten definition(not computable)

Graph structure:necessaryconditions

formal(computable)

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Relationships and definitions

The set of necessary conditions isdetermined by the graph This can be considered a partial definition

Important considerations: Placement in the graph- selecting parents Appropriate relationships to different

parents True path violation

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Placement inthe graph

Example- Proteasome complex

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The importance of relationships Cyclin dependent protein kinase

Complex has a catalytic and a regulatory subunit How do we represent these activities (function) in

the ontology? Do we need a new relationship type (regulates)?

Catalytic activity

protein kinase activity

protein Ser/Thr kinase activity

Cyclin dependent protein kinase activity

Cyclin dependent protein kinase regulator activity

Molecular_function

Enzyme regulator activity

Protein kinase regulator activity

April 10, 2007

We must avoid true path violations..”the pathway from a child term all the way up to its top-level parent(s) must always be true".

chromosome

Mitochondrialchromosome

Is_a relationship

Part_of relationship

nucleus

April 10, 2007

We must avoid true path violations..”the pathway from a child term all the way up to its top-level parent(s) must always be true".

nucleus chromosome

Nuclearchromosome

Mitochondrialchromosome

Is_a relationshipsPart_of relationship

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GO textual definitions: Related GO terms havesimilarly structured (normalized) definitions

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Structured definitions contain both genusand differentiae

Essence = Genus + Differentiae

neuron cell differentiation =Genus: differentiation (processes whereby a relativelyunspecialized cell acquires the specialized features of..)Differentiae: acquires features of a neuron

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Basis in Reality

GO is designed by a consortium As long as egos don’t get in the way, GO

represents types rather than concepts Large-scale developments of the GO are a result

of compromise Gene Annotators have a large say in GO

content Annotators are experts in their fields Annotators constantly read the scientific literature

But, since GO is representing a science, GO actually represents paradigms.

Therefore, it is essential that GO is able to change!

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Types and Instances

For the sake of GO, types are theterms and instances are the gene

product attributes that areannotated to them.

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Types and Instances

When should we create a new type asopposed to multiple annotations?

When the the biology represents auniversal principal. Receptor signalingprotein tyrosine kinase activity does notrepresent receptor signaling proteinactivity and tyrosine kinase activityindependently.

April 10, 2007

Ontology alignmentOne of the current goals of GO is to align:

cone cell fate commitment retinal_cone_cell

keratinocyte differentiation keratinocyte

adipocyte differentiation fat_cell

dendritic cell activation dendritic_cell

lymphocyte proliferation lymphocyte

T-cell homeostasis T_lymphocyte

garland cell differentiation garland_cell heterocyst cell differentiation heterocyst

Cell Types in GO Cell Types in the Cell Ontologywith

April 10, 2007

Alignment of the Two Ontologies will permit thegeneration of consistent and complete definitions

id: CL:0000062name: osteoblastdef: "A bone-forming cell which secretes an extracellular matrix.Hydroxyapatite crystals are then deposited into the matrix to formbone." [MESH:A.11.329.629]is_a: CL:0000055relationship: develops_from CL:0000008relationship: develops_from CL:0000375

GO

Cell type

New Definition

+

=Osteoblast differentiation: Processes whereby anosteoprogenitor cell or a cranial neural crest cellacquires the specialized features of an osteoblast, abone-forming cell which secretes extracellular matrix.

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Alignment of the Two Ontologies willpermit the generation of consistent

and complete definitionsid: GO:0001649

name: osteoblast differentiationsynonym: osteoblast cell differentiationgenus: differentiation GO:0030154 (differentiation)differentium: acquires_features_of CL:0000062 (osteoblast)definition (text): Processes whereby a relatively unspecialized cellacquires the specialized features of an osteoblast, the mesodermalcell that gives rise to bone

Formal definitions with necessary and sufficientconditions, in both human readable and computerreadable forms

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Other Ontologies that can bealigned with GO

Chemical ontologies 3,4-dihydroxy-2-butanone-4-phosphate synthase activity

Anatomy ontologies metanephros development

GO itself mitochondrial inner membrane peptidase activity

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But Eventually…

April 10, 2007

Building Ontology

Improve

Collaborateand Learn

April 10, 2007

A tribute to Lewis CarrollOnce master the machinery of Symbolic Logic, and you have a mentaloccupation always at hand, of absorbing interest, and one that will be ofreal use to you in any subject you may take up. It will give you clearness ofthought - the ability to see your way through a puzzle - the habit ofarranging your ideas in an orderly and get-at-able form - and, morevaluable than all, the power to detect fallacies, and to tear to pieces theflimsy illogical arguments, which you will so continually encounter inbooks, in newspapers, in speeches, and even in sermons, and which soeasily delude those who have never taken the trouble to master thisfascinating Art.Lewis Carroll

(a) All babies are illogical.(b) Nobody is despised who can manage a crocodile.(c) Illogical persons are despisedCan a baby can manage a crocodile?