the unbearable lightness of biomedical informatics

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The Unbearable Lightness of Biomedical Informatics

Barry Smith

Saarbrücken/Buffalo

http://ontologist.com

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if Medical WordNet* is the solution

what is the problem?

*Coling Proceedings, Vol. 1, pp. 371-380

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Cerebellar tumor

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DNA

Protein

Organelle

Cell

Tissue

Organ

Organism

10-5 m

10-1 m

10-9 m

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The quantity-quality divide30,000 genes in human200,000 proteins100s of cell types100,000s of disease types 1,000,000s of biochemical pathways (including

disease pathways)

… legacy of Human Genome Project… and of attempts to institute the electronic

health record

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DNA

Protein

Organelle

Cell

Tissue

Organ

Organism

10-5 m

10-1 m

10-9 m

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FUNCTIONAL GENOMICS

proteomics,

reactomics,

metabonomics,

toxicopharmacogenomics

phenomics,

behaviouromics,

…

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DNA

Protein

Organelle

Cell

Tissue

Organ

Organism

10-5 m

10-1 m

10-9 m

The method of annotations

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DNA

Protein

Organelle

Cell

Tissue

Organ

Organism

10-5 m

10-1 m

10-9 m

The method of indexing

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The Gene Ontology

menopause

sensitivity to blue light

heptolysis

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How overcome incompatibilities between different scientific index

terms?

immunology

genetics

cell biology

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One answer (statistical) computational linguistics

Pattern recognition based on string searches

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String searches need constraints

we can’t leave it to luck to overcome terminological incompatibilities

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Remember –different disciplines are using different terminologies to refer to the same

objects, processes, features in reality

immunology

genetics

cell biology

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An alternative answer:

“Ontology”

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Ontology, roughly:

Overcome terminological incompatibilities by creating a standardized framework into which diverse vocabularies can be mapped

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Kinds of Ontologies

Terms

General Logic

Thesauri

formalTaxonomies

Frames(OKBC)

Data Models(UML, STEP)

Description Logics

(DAML+OIL)

Principled, informal

hierarchies

ad hoc Hierarchies

(Yahoo!)structured Glossaries

XML DTDs

Data Dictionaries

(EDI)

‘ordinary’Glossaries

XML Schema

DB Schema

Glossaries & Data Dictionaries

MetaData,XML Schemas, & Data Models

Formal Ontologies & Inference

Thesauri, Taxonomies

Michael Gruninger

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Kinds of Ontologies

A shared vocabulary plus a specification of its intended meaning

meaning specifiedexplicitly in a logically rigorous way

Two extremes

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Kinds of Ontologies

Terms

General Logic

Thesauri

formalTaxonomies

Frames(OKBC)

Data Models(UML, STEP)

Description Logics

(DAML+OIL)

Principled, informal

hierarchies

ad hoc Hierarchies

(Yahoo!)structured Glossaries

XML DTDs

Data Dictionaries

(EDI)

‘ordinary’Glossaries

XML Schema

DB Schema

Glossaries & Data Dictionaries

MetaData,XML Schemas, & Data Models

Formal Ontologies & Inference

Thesauri, Taxonomies

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Kinds of Ontologies

A shared vocabulary plus a specification of its intended meaning

meaning specifiedexplicitly in a logically rigorous way

Too expensive

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Kinds of Ontologies

A shared vocabulary plus a specification of its intended meaning

Meaning specified informally via natural

language

Two extremes

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Work on biomedical ontologies grew out of work on medical thesauri and nomenclatures

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Kinds of Ontologies

Terms

General Logic

Thesauri

formalTaxonomies

Frames(OKBC)

Data Models(UML, STEP)

Description Logics

(DAML+OIL)

Principled, informal

hierarchies

ad hoc Hierarchies

(Yahoo!)structured Glossaries

XML DTDs

Data Dictionaries

(EDI)

‘ordinary’Glossaries

XML Schema

DB Schema

Glossaries & Data Dictionaries

MetaData,XML Schemas, & Data Models

Formal Ontologies & Inference

Thesauri, Taxonomies

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Fruit

Orange

Vegetable

similarTo

ApfelsinesynonymWith

NarrowerTerm

Graph with labels edges (similarTo, Narrower, synonymWith)Fixed set of edge labels (a.k.a. relations)

Goble & Shadbolt

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Unified Medical Language System (UMLS)

UMLS Metathesaurus:

1 million biomedical concepts

2.8 million concept names

from more than 100 controlled vocabularies and classifications

built by US National Library of Medicine

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UMLS Source Vocabularies

MeSH – Medical Subject Headings

…

ICD International Classification of Diseases

…

GO – Gene Ontology

…

FMA – Foundational Model of Anatomy

…

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To reap the benefits of standardization

we need to make ONE SYSTEM out of many different terminologies

= UMLS “Semantic Network”nearest thing to an “ontology” in the UMLS

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UMLS SN

Alexa McCray, “An Upper Level Ontology for the Biomedical Domain”, Comparative and Functional Genomics, 4 (2003), 80-84.

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UMLS SN

134 Semantic Types

54 types of edges (relations)

yielding a graph containing more than 6,000 edges

32Fragment of UMLS SN

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UMLS SN Top Level

entity event

physical conceptual object entity

organism

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conceptual entity

Organism Attribute

Finding

Idea or Concept

Occupation or Discipline

Organization

Group

Group Attribute

Intellectual Product

Language

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conceptual entity

Organism Attribute

Finding

Idea or Concept

Occupation or Discipline

Organization

Group

Group Attribute

Intellectual Product

Language

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Idea or ConceptFunctional ConceptQualitative ConceptQuantitative ConceptSpatial Concept

Body Location or RegionBody Space or JunctionGeographic AreaMolecular Sequence

Amino Acid SequenceCarbohydrate SequenceNucleotide Sequence

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Idea or ConceptFunctional ConceptQualitative ConceptQuantitative ConceptSpatial Concept

Body Location or RegionBody Space or JunctionGeographic AreaMolecular Sequence

Amino Acid SequenceCarbohydrate SequenceNucleotide Sequence

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Idea or ConceptFunctional ConceptQualitative ConceptQuantitative ConceptSpatial Concept

Body Location or RegionBody Space or JunctionGeographic AreaMolecular Sequence

Amino Acid SequenceCarbohydrate SequenceNucleotide Sequence

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Idea or ConceptFunctional ConceptQualitative ConceptQuantitative ConceptSpatial Concept

Body Location or RegionBody Space or JunctionGeographic AreaMolecular Sequence

Amino Acid SequenceCarbohydrate SequenceNucleotide Sequence

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Lake Geneva

is an Idea or Concept

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Idea or ConceptFunctional ConceptQualitative ConceptQuantitative ConceptSpatial Concept

Body Location or RegionBody Space or JunctionGeographic AreaMolecular Sequence

Amino Acid SequenceCarbohydrate SequenceNucleotide Sequence

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UMLS

Fingers is_a Body Location or Region

Hand is_a Body Part, Organ, or Organ Component

hand part_of body

BUT NOT

fingers part_of hand

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Problem: Running together of concepts and entities in reality

bioinformatics à la UMLS SN( like many “knowledge engineering” disciplines )

floats free from reality in a conceptual world

of its own creation

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Blood Pressure OntologyThe hydraulic equation:

BP = CO*PVR

arterial blood pressure (BP) is directly proportional to the product of blood flow (cardiac output, CO) and peripheral vascular resistance (PVR).

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UMLS SN

blood pressure is an Organism Function

cardiac output is a Laboratory or Test Result or Diagnostic Procedure

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BP = CO*PVR thus asserts that

blood pressure is proportional either to a laboratory or test result or to a diagnostic procedure

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Problem: Confusion of reality with our (ways of gaining) knowledge

about reality

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UMLS Semantic Network

entity

physical conceptual object entity

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Physical Object

Substance

Food Chemical Body

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Chemical

Chemical Chemical

Viewed Viewed

Structurally Functionally

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Problem: Confusion of objects with our ways of referring to

objects

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Chemical

Chemical ChemicalViewed Viewed

Structurally Functionally

Inorganic Organic Enzyme Biomedical or Chemical Chemical Dental Material

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This multiple inheritance leads to errors in coding

Gene Ontology will eliminate multiple inheritance

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UMLS Semantic Network

entity

physical conceptual object entity

organism

is_a

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UMLS SN

is_a =def.

If one item ‘is_a’ another item then the first item is more specific in meaning than the second item. (Italics added)

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fish is_a vertebrate

copulation is_a biological process

both testes is_a testis

Nazi is_a Nazism

plant parts is_a plant

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What are the nodes in this graph?

Almost all nodes are linked to other nodes by a multiplicity of different types of edges

Compare: swimming is healthy

swimming has 8 letters

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Semantic Network Definition:

Concept =def. An abstract concept, such as a

social, religious, or philosophical concept

UMLS Definition:

Concept =def. A class of synonymous terms

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How can concepts figure as relata of these relations?

part_of = def. Composes, with one or more other physical units, some larger whole

causes =def. Brings about a condition or an effect.

contains =def. Holds or is the receptacle for fluids or other substances.

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How can a set of synonymous terms serve as a receptacle for fluids or other substances?

How can sets of synonymous terms stand in relations such as affects or causes?

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connected_to =def. Directly attached to another physical unit as tendons are

connected to muscles.

How can a concept be directly attached to another physical unit?

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What are the relata which are linked by the edges in the SN

graph?

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To answer this question

we need to distinguish clearly between concepts and classes:

concepts are creatures of cognition

classes are invariants (types, kinds, universals) out there in reality

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If ontologies are about meanings / concepts

it becomes impossible to deal coherently with those relations between entities in reality which involve appeal to both classes and their instances.

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Illustration re: part_of

heart part_of human

human heart part_of human

testis part_of human

human testis part_of human

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For instances:part_of = instance-level parthood

(for example between Mary and her heart)

For classesA part_of B =def. given any instance a of A

there is some instance b of B such that a part_of b

This is an assertion about As.

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a adjacent_to b

(instance-level adjacency, for example between Mary’s head and Mary’s neck)

For classes:

A adjacent_to B =def. given any instance a of A there is some instance b of B which is such that a adjacent_to b

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A adjacent_to B

as an assertion about classes

is never an assertion about As exclusively

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A adjacent_to B =def.

given any instance a of A there is some instance b of B which is such that a adjacent_to b

and

given any instance b of B there is some instance a of A which is such that a adjacent_to b

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Almost all of the 54 types of edges in SN are dealt with

incoherently

part_of HAS INVERSE has_part

nucleus part_of cell

cell has_part nucleus

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Acquired Abnormality affects FishExperimental Model of Disease affects

FungusFood causes Experimental Model of

DiseaseBacterium causes Experimental Model of

DiseaseBiomedical or Dental Material causes

Mental or Behavioral Dysfunction Manufactured Object causes Disease or

SyndromeVitamin causes Injury or Poisoning

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How to do better?

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How to do better?How to create a network of biomedically relevant terms/classes, with coherently defined relations between them, to which expert terms of the UMLS can be assigned in a maximally intelligible way?

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What linguistic framework

is shared in common by immunologists, geneticists and cell biologists,

by phenobehavioromists and by toxicopharmacogenomists?

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Answer:

the natural language they all use to talk about biological (biomedical) phenomena

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BioWordNetjoint work with

Christiane Fellbaum

(see paper in Proceedings)

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BioWordNet

use WordNet’s biomedical vocabulary, to create a better alternative to UMLS SN

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Strengths of WordNet 2.0

Open source

Very broad coverage

Is-a / part-of architecture

Tool for automatic sense disambiguation

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Weaknesses of WordNet 2.0Problems with relationsMixes up expert and non-expert vocabularyErrorsGapsNoise

all prevent WordNet’s being used in scientific context as substitute for UMLS SN

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Fix WordNet’s relations by using the methodology outlined above

already applied to:

Foundational Model of Anatomy

Gene Ontology

Open Biological Ontologies

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Institute for Formal Ontology and Medical Information Science

Saarbrücken

http://ifomis.org

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WordNet mixes up expert and non-expert vocabulary,

both current and medieval:

suppuration#2 {pus, purulence, suppuration, ichor, sanies, festering}

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WordNet contains biomedically relevant errors

snore-sleep

WordNet: if someone snores, then he necessarily also sleeps

snoring = the respiratory induced vibration of glottal tissues

associated not only with sleep but also with relaxation or obesity

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WordNet has too much noise for purposes of scientific applications

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13 senses for feel is a verbexperience – She felt resentfulfind – I feel that he doesn't like mefeel – She felt small and insignificant; feel – We felt the effects of inflationfeel – The sheets feel softgrope –He felt for his walletfinger – Feel this soft cloth! explore – He felt his way around the dark room)feel – It feels nice to be home againfeel – He felt the girl in the movie theater)

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Medical senses of ‘feel’

palpate – examine a body part by palpation:

The runner felt her pulse.

sense – perceive by a physical sensation, e.g. coming from the skin or muscles:

He felt his flesh crawl

feel – seem with respect to a given sensation:

My cold is gone – I feel fine today

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WordNet has gaps even in its coverage of biomedical natural

language

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WordNet seness of ‘regulation’1. regulation (ordinance, rule)2. rule, regulation -- (a principle that customarily governs behavior; "short haircuts were the regulation")3. regulation -- (the state of being controlled or governed)4. regulation -- (the ability of an early embryo to continue normal development after its structure has been somehow damaged)5. regulation, regularization, regularisation -- (the act of bringing to uniformity)6. regulation, regulating -- (the act of controlling according to rule; "fiscal regulations are in the hands of politicians")

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Biological sense of ‘regulation’:

A process that modulates the frequency, rate or extent of behavior

(Gene Ontology)

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WordNet senses of ‘inhibition’1. inhibition, suppression -- ((psychology) the conscious exclusion of unacceptable thoughts or desires)2. inhibition -- (the quality of being inhibited)3. inhibition -- the process whereby nerves can retard or prevent the functioning of an organ or part; "the inhibition of the heart by the vagus nerve")4. prohibition, inhibition, forbiddance -- (the action of prohibiting or forbidding)

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Biological senses of ‘inhibition’ much broader

inhibition = negative regulation

enzymes can be inhibited

reactions can be inhibited

… and not only by nerves

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WordNet senses of ‘binding’1. binding -- (the capacity to attract and hold something)2. binding -- (a strip sewn over or along an edge for reinforcement or decoration)3. dressing, bandaging -- (the act of applying a bandage)4. binding, book binding; "the book had a leather binding")

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biological sense of ‘binding’

interacting selectively with

(Gene Ontology)

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Remove errors, noise and gaps in a two-stage process

1.select biomedically relevant natural-language terms from WordNet 2.0 extended by standard biomedical information sources

2.validate these terms and the relations between them

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Validationeach arc in BWN is converted into a natural-

language sentence

e.g. ‘mumps is an inflammation’

via controlled human subjects experiments:

are accredited

1. as intelligible by non-experts

2. as true by experts

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we use logical methods to ensure a coherent treatment of BWN’s

upper-level classes and relations

and thereby also bring logical rigor in a practical fashion to the

whole of the UMLS Metathesaurus

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Bring ontological rigour to BWN

Terms

General Logic

Thesauri

formalTaxonomies

Frames(OKBC)

Data Models(UML, STEP)

Description Logics

(DAML+OIL)

Principled, informal

hierarchies

ad hoc Hierarchies

(Yahoo!)structured Glossaries

XML DTDs

Data Dictionaries

(EDI)

‘ordinary’Glossaries

XML Schema

DB Schema

Glossaries & Data Dictionaries

MetaData,XML Schemas, & Data Models

Formal Ontologies & Inference

Thesauri, Taxonomies

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The long-term goal

BWN should serve as scaffolding/indexing system for the much larger and denser net of expert biomedical terminology which is the UMLS Metathesaurus

104The End