From chemicals to minds: Integrated ontologies in the search for scientific understanding
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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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From chemicals to minds: Integrated ontologies in the search for scientific understanding
- 1. InterOntology @ Tokyo, February 2012 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
- 2. I want… 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 I think… linked to sociopathy, psychopathy, narcissism and general manipulativeness. Tuesday, February 28, 2012 2
- 3. Bio-ontologies serve many purposes Standards … 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 Tuesday, February 28, 2012 3
- 4. Tuesday, February 28, 2012 4
- 5. ChEBI is an ontology of small molecules ChEBI Ontology chemical entity role chemical substance biological role molecular entity application group chemical role carbonyl compound pharmaceutical solvent carboxy group carboxylic acid antibacterial drug cyclooxygenase has part inhibitor has role cefpodoxime (CHEBI:606443) Tuesday, February 28, 2012 5
- 6. 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 reconstruction e.g. for scaffold hopping in drug discovery Tuesday, February 28, 2012 6
- 7. Pathways and metabolic network reconstructions encode dynamic biochemical knowledge Tuesday, February 28, 2012 7
- 8. 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] Tuesday, February 28, 2012 8
- 9. ChEBI is manually maintained by a team of chemists ChEBI growth: no. of entries 30,000 25,000 20,000 15,000 10,000 5,000 0 Jun-08 Apr-09 Sep-09 Feb-10 Dec-10 Jan-08 Nov-08 Jul-10 Oct-11 May-11 Tuesday, February 28, 2012 9
- 10. Classification practices in chemistry lead to massive multiple inheritance ChEBI ontology 10
- 11. Tuesday, February 28, 2012 11
- 12. 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; Tuesday, February 28, 2012 12
- 13. 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
- 14. tricarboxylic acid equivalentTo molecule and has_functional_group exactly 3 carboxy group 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) ChEBI ontology 14
- 15. 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 15
- 16. ChEBI ‘roles’ represent how chemicals act Subatomic particle: parts of atoms Chemical entity: parts and structural features of molecules ‘Has role’ Role ontology: active properties of chemical entities
- 17. 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) 17
- 18. Examples of chemical dispositions • Buffer • Surfactant • Catalyst • Antioxidant • Hydrogen donor / • Detergent acceptor • De-aminating agent • Acid / base • Radical scavenger 18
- 19. Biological functions • Epitope ChEBI functions are the • Mitogen ‘other side’ of the GO molecular functions • Hormone (which have protein • Growth regulator bearers) • Toxin • Nutrient Both functions are • COX inhibitor realized in the same • Cholinesterase process reactivator 19
- 20. Artefactual functions • Label Chemicals are designed • Fragrance synthetically or selected by chemists in order to • Pesticide perform certain functions • Fuel outside of biological • Dye evolution • Detergent • Probe But what about • Reagent drugs, e.g. for treatment • Agrochemical of headaches? 20
- 21. 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
- 22. 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, 22 but it kills cats
- 23. Bridging from chemistry to biology Some 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)
- 24. ChEBI is now the (behind-the-scenes) chemical representation of all the chemical biology GO:0051610 in GO The directed movement (to be published soon!) of serotonin into a cell
- 25. A very interesting class of molecules: those that alter mental functioning Tuesday, February 28, 2012 25
- 26. Mental Functioning Ontology (MFO) BFO:Entity BFO BFO:Continuant BFO:Occurrent MFO BFO:Independent BFO:Dependent BFO:Process Continuant Continuant Bodily Process Organism BFO:Disposition Cognitive Representation BFO:Quality Mental Functioning Mental Process Related Anatomical Structure Behaviour inducing state Affective Representation Tuesday, February 28, 2012 26
- 27. How does mental functioning actually work? EEG Biology Mouse Psychology Human Physics fMRI Genetic profiling Gene Neuroscience expression analysis Psychiatry Metabolic Chemistry Self-reports analysis Questionnaires
- 28. 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
- 29. Existing vocabularies don’t include computable definitions
- 30. The Emotion Ontology (MFO-EM) BFO:Entity BFO MFO BFO:Continuant BFO:Occurrent MFO-EM BFO:Independent BFO:Dependent Continuant Continuant BFO:Process Organism BFO:Disposition Bodily Process Physiological Response to Emotion Process Mental Process Cognitive inheres_in Representation Appraisal Process Emotional Action Tendencies Affective is_output_of Representation Appraisal Emotional Behavioural Process Subjective Emotional Feeling has_part agent_of Emotion Occurrent
- 31. Types of emotion Tuesday, February 28, 2012 31
- 32. To define the characteristics of different emotions start with canonical emotions Emotion types (such as fear) show enormous variance across instances Just 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 Has part appraisal Has output Appraisal of fear process dangerousness Canonical fear results from an appraisal of dangerousness Tuesday, February 28, 2012 32
- 33. Canonical fear fear subtype canonical fear EMOTION COMPONENT CHARACTERISTIC FOR FEAR Action tendency Fight-or-flight Subjective emotional feeling Negative, tense, powerless Behavioural response Characteristic fearful facial expression Characteristic appraisal Something is dangerous to me Tuesday, February 28, 2012 The Emotion Ontology (ICBO 2011) 33
- 34. 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 Tuesday, February 28, 2012 34
- 35. Cognitive Neuroscience of Emotion Task Classification in MFO/MFOEM Recognition of gender in emotional facial Visual perception of emotional facial expressions expressions (subClassOf perception) Recall of personal emotional memories Memory of emotional episodes with instructions to try re-create feeling (subClassOf memory) Listening to emotional sounds (e.g. grunts Auditory perception of emotional stimuli of disgust) (subClassOf perception) Viewing emotional film extracts Visual and auditory perception of emotional stimuli (subClassOf perception) Paradigms selected based on study of random sample of papers 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 Tuesday, February 28, 2012 35
- 36. (Part of) the biochemical basis of emotion is in ChEBI Emotions are effected in part by neurotransmitters such as dopamine, tryptophan molecular entity biological role Molecular function emotion (CHEBI:25375) (CHEBI:24432) (GO:0003674) (MFOEM:1) subtype neurotransmitter happiness dopamine neurotransmitter receptor activity (MFOEM:42) (CHEBI:25375) (CHEBI:25512) (GO:0030594) has role realized in part of Tuesday, February 28, 2012 36
- 37. Disorders of affect Some mental diseases involve altered emotional functioning. (E.g. depression, bipolar disorder) Disposition Process mental emotion biological process disease Mechanism of action: complex down-regulation disturbances in non-canonical of dopaminergic depression underlying sadness system systems (GO:0032227) realized in has part Tuesday, February 28, 2012 37
- 38. 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 Tuesday, February 28, 2012 38
- 39. 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; … Tuesday, February 28, 2012 39
- 40. Conclusions Bio-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 Tuesday, February 28, 2012 40
- 41. Acknowledgements Mental Functioning and Emotion Ontologies: Kevin Mulligan (UNIGE), Barry Smith & Werner Ceusters (Buffalo) ChEBI: Paula de Matos, Christoph Steinbeck, Colin Batchelor (RSC), Stefan Schulz (Graz) Funding BBSRC (UK), NSF (CH), EU-OPENSCREEN Tuesday, February 28, 2012 41
Hinweis der Redaktion
- By the end of this talk, I hope to have convinced you that studying chemicals and minds .. And doing so via bio-ontology .. Are a perfectly sensible combination. I will give an overview “report from the front lines” of some of the practical bio-ontology projects that I am involved in, distributed across computer science, philosophy and domain science; distributed across the relatively mature ChEBI project to the fledgling MFO project.
- I am not a chemist… ChEBI is my external chemical brain!
- ChEBI was introduced in order to address the standardisation of chemical annotation across bioinformatics databases… i.e. the equivalent of the Gene Ontology but for chemistry within a biological context. And it does serve that purpose: many different databases use ChEBI as their chemical annotation resource. But like other bio-ontologies, it serves many other purposes by now. One of those is to be my external chemistry brain. I don’t know chemistry, and I don’t have to (for my purposes): ChEBI knows chemistry, and I know how to ask ChEBI questions.
- ChEBI is manually curated. Chemicals are given a structure-based classification and assigned with the has_role relationship to the role ontology.
- From Swainston et al., Subliminal toolbox (http://dbkgroup.org/Papers/swainston_subliminal_jib11.pdf)See also: http://www.slideshare.net/neilswainston/chebi-and-genome-scale-metabolic-reconstructions
- ChEBI is manually curated and growth rate is slow… show a picture of an unhappy person waiting in the line to get their chemical annotated…
- This is a good argument for why ontology is useful in chemistry. Chemoinformatics is full of systems to automatically classify compounds based on their structural features. The problem is that you need a new algorithm – or a new trained statistical model – for each different problem, and this does not in any way render the result accessible to domain experts, nor provide explanations of predictions.
- Higher expressivity is not necessarily required for question answering, since the inferred hierarchy can be exported to OWL-EL for question answering.
- This is BFO terminology
- The history of bio-ontologies is part of the open data movement in bioinformatics. The Gene Ontology: most successful bio-ontology. Many others exist: phenotypes, chemicals, anatomy, cells, proteins…The OBO Foundry: a coordinating organisation which brings together bio-ontologists to address matters of interoperability and integration(Controlled vocabularies give you the benefit of standards without the benefits of AI)So that researchers don’t have to spend their time doing data integration
- There are 134 hits for ‘has role’ some psychotropic in ChEBI in February 2012. This screenshot (inter alia) shows Lithium (a mood stabilizer); chlorpromazine (an antipsychotic); valproate (antimanic); 5-methoxy-N,N-dimethyltryptamine (hallucinogen);
- Mental functioning related anatomical structure: an anatomical structure in which there inheres the disposition to be the agent of a mental processBehaviour inducing state: a bodily quality inhering in a mental functioning related anatomical structure which leads to behaviour of some sortAffective representation: a cognitive representation sustained by an organism about its own emotionsCognitive representation: a representation which specifically depends on an anatomical structure in the cognitive system of an organismMental process: a bodily process which brings into being, sustains or modifies a cognitive representation or a behaviour inducing state
- (Not the million dollar question, but the many billion dollars question!)We’re drowning in data and starving for knowledge! Not only different domains BUT different methods and different subjects (model organisms etc)Huge piles of different sorts of information coming out of different research areas. DIFFERENT PERSPECTIVES: if you try to get people to agree on names, they just don’t. But give them semantics-free identifiers and their own preferred (scoped) synonyms and you can get agreement on the definitions. Nobody is an expert in everything, most scientists are stuck in their narrow area of focus and expertise (which is a good thing for progress because you HAVE to become that specialised)
- Different interpretations for the same results can ensue; based on the underlying theory of mental functioning. Linking the theory directly to the paradigm (tests) and the research results allows more straightforward generation of testable hypothesis for evaluating different theories… getting away from conceptual arguments, or at least helping to resolve them(Explicit logical formulation)
- SNOMED, MeSH, ICD, ICF, Cognitive Atlas, Cognitive Paradigm Ontology, We will build on these vocabulary resources as sources, but maintain links so that we don’t lose mappings which have already been annotated to these sources.Most of these sources maintain controlled vocabularies but not real ontologies. There is a shortage of explicit relationships and formal (computable) definitions, so you can’t infer anything from annotations and you can’t link between different resources.
- Canonical fear also involves an action tendency to fight-or-flight, a bad (powerless, negative, anxious) feeling, a behavioural response to the emotion that includes a characteristic fearful facial expression
- Cognitive neuroscience uses research “paradigms” – experimental designs intended to allow comparison of brain activation between different conditions. The subtraction of the brain activation for the control condition from the brain activation for the test condition then gives the “net” activation, which is what is reported on in the literature, subject to statistical analysis.
- This is, of course, just one tiny part of the story. The overall story would have to be built up out of many, many cross-ontology links.
- Depression and bipolar disorder are paradigm affective disorders.
- Linking entities in ontologies describing mental disease to the entities describedin ontologies for the underlying mechanism of action such as chemicals and proteinsthus allows automated retrieval of biological knowledge in relevant databases and au-tomated linking of these data to the corresponding medical and psychiatric data intoaddiction. For one example of the enhanced querying capability that results from theabove described chain of interlinkages to describe the biochemistry and neurobiologyof addiction: rather than querying the pathway databases for heroin alone, a query canretrieve results for all molecules that act with the same mechanism of action (22 dif-ferent molecules are annotated as has role `-opioid receptor agonist' (CHEBI:55322)in the January 2012 release of ChEBI).The life sciences still hold many mysteries at all of the dierent levels from thevery small to the very large { from the processes at the biochemical level that controlDNA replication and cellular metabolism to the complicated synchronization of thefunctioning of whole organisms. Alongside the need to interpret data at all levels,there is a need for integration between the different levels, to achieve a holistic viewacross everything that is currently known. This is the vision of whole-systems biology,and computational processing is essential in making that vision into a reality. Butthe computational processing needs to be guided by a very special structure { thatis, it needs to be guided by our best understanding of what the entities are that thescience is about. Only by focusing on what the science is about, on what is known tohold in the world that science tries to study, can scientific results be integrated acrossdifferent technological platforms, across different research programs, across differentmountains of raw data, and across conflicting and sometimes bewildering results. Afurther necessary condition is that ontologies for different domains are able to workwell together.
- Interlinking ontologies provides many good things: automated bridging across levels of granularity for representation of modes of action; indexing; querying; aggregation; comparison of results across disciplines.
- Scientists are ants, each contributing a tiny amount to the knowledge that humans collectively possess about the world. Bio-ontology aims to computably represent that knowledge since it is greater than any one person can amass – across all the domains, across all the different fields, across all the different levels and granularities. Computers become our external minds – but they need to be much better at being external minds – and they need to be able to do it in a global, cross-disciplinary fashion.