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From Chemicals to Minds: Integrated ontologies in the search for scientific understanding Janna Hastings 1,2 1 Cheminformatics and Metabolism, European Bioinformatics Institute, UK 2 Swiss Center for Affective Sciences, University of Geneva, Switzerland InterOntology @ Tokyo, February 2012
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From chemicals to minds: Integrated ontologies in the search for scientific understanding

May 11, 2015

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Technology

Janna Hastings

Presented at the 2012 Interdisciplinary Ontology (InterOntology) Conference in Tokyo, February 24th 2012. This presentation gives a whirlwind tour of some "reports from the front lines" of practical bio-ontology development in ChEBI and in the Mental Functioning and Emotion Ontology projects.
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Page 1: From chemicals to minds: Integrated ontologies in the search for scientific understanding

From Chemicals to Minds:

Integrated ontologies in the search for scientific understanding

Janna Hastings1,2

1 Cheminformatics and Metabolism, European Bioinformatics Institute, UK

2 Swiss Center for Affective Sciences, University of Geneva, Switzerland

InterOntology @ Tokyo, February 2012

Page 2: From chemicals to minds: Integrated ontologies in the search for scientific understanding

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Oxytocin is believed to play a role in various behaviors, including orgasm, social recognition, pair bonding, anxiety … it is sometimes referred to as the "love hormone".

The inability to secrete oxytocin and feel empathy is linked to sociopathy, psychopathy, narcissism and general manipulativeness.

I want…

I think…

Page 3: From chemicals to minds: Integrated ontologies in the search for scientific understanding

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Bio-ontologies serve many purposesStandards … for automated data exchange in rapidly changing scientific environments

Categorisation of entities in the domain … for data-driven research such as functional analysis of gene transcription

Facilitating interdisciplinary research through enabling comparison of results across disciplines

Representing what we know about science

Page 4: From chemicals to minds: Integrated ontologies in the search for scientific understanding

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Page 5: From chemicals to minds: Integrated ontologies in the search for scientific understanding

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ChEBI is an ontology of small molecules

ChEBI Ontology

chemical entity role

carboxylic acid

application

antibacterial drug

cefpodoxime (CHEBI:606443)

pharmaceutical

biological role

chemical role

chemical substance

molecular entitygroup

carbonyl compoundsolvent

has role

cyclooxygenaseinhibitor

carboxy group

has part

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Why do people want their chemicals annotated in ChEBI?

ChEBI is the only freely available chemical database with high-quality manual curation

ChEBI IDs are stable and maintained

ChEBI ontology allows automatic traversal and retrieval of chemical knowledge

e.g. for metabolic network reconstructione.g. for scaffold hopping in drug discovery

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Pathways and metabolic network reconstructions encode dynamic biochemical knowledge

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ChEBI and Metabolic Network Reconstruction

1.Fuzzy merging between different models for integrated view on patchy knowledge , uses nearest shared ancestor

2.Protonation state of metabolites important for charge balancing, uses conjugate base / acid relationships

3.Proper treatment of biomass reactions (searches for “is a” lipid relationship

[Swainston et al, Manchester]

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ChEBI is manually maintained by a team of chemists

Jan-08

May

-08

Sep-08

Jan-09

May

-09

Sep-09

Jan-10

May

-10

Sep-10

Jan-11

May

-11

Sep-11

Jan-12

0

5,000

10,000

15,000

20,000

25,000

30,000

ChEBI growth: no. of entriesLong wishlist

from users

Page 10: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Classification practices in chemistry lead to massive multiple inheritance

ChEBI ontology

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Page 12: From chemicals to minds: Integrated ontologies in the search for scientific understanding

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Desiderata for structure-based automated classification

Class definitions should be expressed in a language or formalism which is accessible to domain experts (chemists);

It should be possible to combine different elementary features into sophisticated class definitions using compositionality;

The specification of class definitions should allow automatic arrangement of those classes into a hierarchy

Mid-level groupings should be semantic, i.e. they should make sense to chemists and be named;

Page 13: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Logical definitions enable automatic classification

hydrocarbon equivalentTo molecule and has_atom only

(carbon atom or hydrogen atom)

peptide cation equivalentTo peptide and has_charge some double

[>, 0.0]

ChEBI ontology

13

Value restriction

Data range restriction

Page 14: From chemicals to minds: Integrated ontologies in the search for scientific understanding

ChEBI ontology

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tricarboxylic acid equivalentTo molecule and has_functional_group exactly 3

carboxy group Cardinality restriction (but in practice: use data value restriction)

Beyond OWL

Structured object representation & reasoning (Magka et al., Oxford)

Hybrid reasoning with second-order features of symmetric graphs such as fullerenes (Kutz et al., Bremen)

Page 15: From chemicals to minds: Integrated ontologies in the search for scientific understanding

What about non-structural classes?

All sulphuric acid molecules have a sulphur atom and four oxygen atoms arranged in a certain bonding pattern at all times that they exist.

But any given molecule may or may not ever be involved in acting as a strong acid

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Page 16: From chemicals to minds: Integrated ontologies in the search for scientific understanding

ChEBI ‘roles’ represent how chemicals act

Subatomic particle: parts of atoms

Chemical entity:parts and structural features of molecules

Role ontology:active properties of chemical entities

‘Has role’

Page 17: From chemicals to minds: Integrated ontologies in the search for scientific understanding

ChEBI ‘roles’ are BFO realizables (mostly)

Properties that we ascribe to things because of what can happen under certain circumstances (future-pointing) are called realizable entities

The processes (/events) in which they display those properties are called realizations

(the property, however, exists all the time)

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Page 18: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Examples of chemical dispositions

• Buffer • Catalyst• Hydrogen donor /

acceptor• Acid / base

• Surfactant• Antioxidant• Detergent• De-aminating agent• Radical scavenger

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Page 19: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Biological functionsChEBI functions are the ‘other side’ of the GO molecular functions (which have protein bearers)

Both functions are realized in the same process

• Epitope• Mitogen• Hormone• Growth regulator• Toxin• Nutrient• COX inhibitor• Cholinesterase

reactivator

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Page 20: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Artefactual functions

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•Label•Fragrance•Pesticide•Fuel•Dye•Detergent•Probe•Reagent •Agrochemical

Chemicals are designed synthetically or selected by chemists in order to perform certain functions outside of biological evolution

But what about drugs, e.g. for treatment of headaches?

Page 21: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Thalidomide is not a drug for treating morning sickness

(anymore)

Originally introduced as a sedative and hypnotic for treatment of morning sickness in 1957, thalidomide was withdrawn from use in the early 1960s after it was shown to produce severe teratogenic effects. It was subsequently found that the (R)-enantiomer is effective against morning sickness, whereas the (S)-enantiomer is teratogenic. However, as the enantiomers can interconvert in vivo, administering only the (R)-enantomer would not prevent the teratogenic effect.

Image credit: Hildeenmikey

Page 22: From chemicals to minds: Integrated ontologies in the search for scientific understanding

A harmless metabolite in one organism is food to another and toxin to a third

Paracetamol treats pain and fever in humans and is safe enough to give to babies,

but it kills cats22

Page 23: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Bridging from chemistry to biologySome ChEBI roles are realized in biological processes

but beware: NOT toxin realized_in ‘response to toxin’

Life cycle of an organism: insecticide realized_in process ‘death’ and has_organism some ‘insect’ (a kind of participation)

Page 24: From chemicals to minds: Integrated ontologies in the search for scientific understanding

GO:0051610The directed movement of serotonin into a cell

ChEBI is now the (behind-the-scenes) chemical representationof all the chemical biologyin GO(to be published soon!)

GO and ChEBI are (nearly)FULLY ALIGNED!

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A very interesting class of molecules: those that alter mental functioning

Page 26: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Mental Functioning Ontology (MFO)

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BFO:Entity

BFO:Continuant BFO:Occurrent

BFO:Process

Organism

BFO:Independent Continuant

BFOMFO

BFO:Dependent Continuant

Behaviour inducing state

Mental Functioning Related Anatomical

Structure

Cognitive Representation

BFO:Quality

Affective Representation

Mental Process

Bodily ProcessBFO:Disposition

Page 27: From chemicals to minds: Integrated ontologies in the search for scientific understanding

How does mental functioning actually work?

Biology

Neuroscience

Chemistry

Psychology

Psychiatry

PhysicsHuman

Mouse

fMRI

Gene expression

analysis

Self-reportsMetabolic analysis

Genetic profiling

EEG

Questionnaires

Page 28: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Theories of mental functioning

Abducted! Replaced!

Capgras delusion: a disorder in which a person holds a delusion that a friend, spouse, parent, or other close family member has been replaced by an identical-looking impostor.

Faulty perception? Normal perception, faulty reasoning? Faulty emotional reaction to perception? Overactive imagination?

TESTABLE IMPLICATIONS

Page 29: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Existing vocabulariesdon’t include

computable definitions

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BFO:Entity

BFO:Continuant BFO:Occurrent

BFO:ProcessBFO:Independent

Continuant

BFOMFO

BFO:Dependent Continuant

Cognitive Representation

Affective Representation

Mental Process

Bodily ProcessBFO:Disposition

MFO-EM

Emotion Occurrent

Organism

Emotional Action Tendencies

Appraisal

Subjective Emotional Feeling

Physiological Response to

Emotion Process

inheres_in

is_output_of

Emotional Behavioural Process

Appraisal Process

has_part

agent_of

The Emotion Ontology (MFO-EM)

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Types of emotion

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To define the characteristics of different emotions start with canonical emotions

Emotion types (such as fear) show enormous variance across instancesJust as do anatomical types, e.g. human bodies

Ontology expresses what is always true… But aims to say something useful for representation of domain knowledge.

Solution: encode such knowledge in ‘canonical’ types

canonical fear

appraisal process

Appraisal of dangerousness

Has part Has output

Canonical fear results from an appraisal of dangerousness

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Canonical fear

The Emotion Ontology (ICBO 2011)

canonical fear

fear

EMOTION COMPONENT CHARACTERISTIC FOR FEARAction tendency Fight-or-flightSubjective emotional feeling Negative, tense, powerlessBehavioural response Characteristic fearful facial

expressionCharacteristic appraisal Something is dangerous to me

subtype

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Canonical and non-canonical fear

Canonical fear gives rise to action tendencies that are conformant to the perceived danger

Phobia = disposition giving rise to non-canonical fear

laridaphobia : intense fear of seagulls

Page 35: From chemicals to minds: Integrated ontologies in the search for scientific understanding

Cognitive Neuroscience of Emotion

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Task Classification in MFO/MFOEM

Recognition of gender in emotional facial expressions

Visual perception of emotional facial expressions (subClassOf perception)

Recall of personal emotional memories with instructions to try re-create feeling

Memory of emotional episodes (subClassOf memory)

Listening to emotional sounds (e.g. grunts of disgust)

Auditory perception of emotional stimuli (subClassOf perception)

Viewing emotional film extracts Visual and auditory perception of emotional stimuli (subClassOf perception)

Paradigms selected based on study of random sample ofpapers from BrainMap database. Conclusion…Cognitive Neuroscience does not usually study canonical emotions! The link from perception of emotional fear in facial expressions to canonical fear is subject to empirical research

Page 36: From chemicals to minds: Integrated ontologies in the search for scientific understanding

(Part of) the biochemical basis of emotion is in ChEBI

Emotions are effected in part by neurotransmitters such as dopamine, tryptophan

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dopamine(CHEBI:25375)

molecular entity (CHEBI:25375)

biological role (CHEBI:24432)

neurotransmitter(CHEBI:25512)

has role

neurotransmitter receptor activity

(GO:0030594)

Molecular function (GO:0003674)

realized in

happiness(MFOEM:42)

part of

emotion(MFOEM:1)

subtype

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Disorders of affectSome mental diseases involve altered emotional functioning. (E.g. depression, bipolar disorder)

emotion

non-canonical sadness

ProcessDisposition

depression

mental disease

realized in

down-regulation of dopaminergic

system (GO:0032227)

has part

biological processMechanism of

action: complex

disturbances in underlying

systems

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Interlinked ontologies accelerate the search for scientific understanding

Linking diseases to mechanisms of action to treatment drugs and biomarkers to genetic factors giving rise to predispositions …

Different disciplines and methods – one reality being investigated

Different types of data – one ontology

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Good ontology design facilitates interlinking

Successfully interlinking ontologies depends on interoperability of the underlying ontologies:

shared technological platform; common upper level; non-overlapping content; agreed bridging relationships; …

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ConclusionsBio-ontology is inescapably interdisciplinary

It needs to be guided by the experts in each domain

The collective goal is to build an interlinked framework of ontologies which describe the best of what is known across the sciences

… in order to provide a knowledge-based backbone for increasingly intelligent and sophisticated computational data analysis and processing techniques

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AcknowledgementsMental Functioning and Emotion Ontologies:

Kevin Mulligan (UNIGE), Barry Smith & Werner Ceusters (Buffalo)

ChEBI: Paula de Matos, Christoph Steinbeck, Colin Batchelor

(RSC), Stefan Schulz (Graz)

FundingBBSRC (UK), NSF (CH), EU-OPENSCREEN