N IF : A C OMPREHENSIVE O NTOLOGY FOR N EUROSCIENCE & P RACTICAL G UIDE FOR D ATA -O NTOLOGY I NTEGRATION Maryann E. MARTONE, Fahim IMAM, Anita Bandrowski, Stephen LARSON, Georgio ASCOLI, Gordon SHEPHERD, Jeffery S. GRETHE, Amarnath GUPTA Univ. of California, San Diego, CA; George Mason Univ., Fairfax, VA; Yale Univ., New Haven, CT February 8, 2011 Funded in part by the NIH Neuroscience Blueprint HHSN C via NIDA. NEUROSCIENCE INFORMATION FRAMEWORK NIFSTD Ontologies neuinfo.org 1

NIF last year NIFSTD Ontologies neuinfo.org 2

NIF today ~30M data records from 68 databases, NIF registry (3600 software tools, databases etc) + full text publication search – Focus of development now is on integration of data with literature – Better search of data (SKOS?) Annotation of data, now automated, will become slightly more manual (we will assert the contents of columns that match parts of ontologies) NIFSTD Ontologies neuinfo.org 3

NIF: D ISCOVER AND UTILIZE WEB - BASED N EUROSCIENCE RESOURCES  A portal to finding and using neuroscience resources  A consistent framework for describing resources  Provides simultaneous search of multiple types of information, organized by category  NIFSTD Ontology, a critical component  Enables concept-based search UCSD, Yale, Cal Tech, George Mason, Harvard MGH Supported by NIH Blueprint NIFSTD Ontologies neuinfo.org 4

NIF ‘dips’ into the lexicon for general searches like ‘cerebellum’ or ‘ontology,’ where users can contribute knowledge, but bring data into the lexicon by using a application that calls our web services

NIF today Ontology-based search – Search requires all search terms: synonyms/acronyms/lexical variation – Added gene: and other : searches are coming (toxin: drug:) – Application logic: String match to multiple ontology terms = bring back all (e.g., striatum and caudate putamen) – Collapse duplicate classes by bridge files: same as relationship (Fahim) – Heavy use of defined classes (GABAergic neuron, hippocampal neuron, drug of abuse etc)

One problem NIF LAMHDI Bioportal NIFSTD Ontologies neuinfo.org 7

Cow example? Description of nose vs. tail: which is more valid? Should they point to the same entity? Is a mapping file the right place to keep the knowledge that class A is related to class B, or should we assert sameness with Mireot? vs.

NIF S TANDARD O NTOLOGIES (N IF S TD ) Set of modular ontologies – Covering neuroscience relevant terminologies – Comprehensive 50,000+ distinct concepts + synonyms Expressed in OWL-DL language Closely follows OBO community best practices – As long as they seem practical Avoids duplication of efforts – Standardized to the same upper level ontologies, e.g., – Basic Formal Ontology (BFO), OBO Relations Ontology (OBO-RO), Phonotypical Qualities Ontology (PATO) – Relies on existing community ontologies e.g., CHEBI, GO, PRO, OBI etc. 9NIF Standard Ontologies Modules cover orthogonal domain e.g., Brain Regions, Cells, Molecules, Subcellular parts, Diseases, Nervous system functions, etc. Bill Bug et al. NIFSTD Ontologies neuinfo.org 9

A BOUT O NTOLOGY “Explicit specification of conceptualization” - Tom Gruber Organizing the concepts involved in a domain into a hierarchy and Precisely specifying how the concepts are ‘related’ with each other (i.e., logical axioms) Explicit knowledge are asserted but implicit logical consequences can be inferred – A powerful feature of an ontology 10NIF Standard Ontologies NIFSTD Ontologies neuinfo.org 10

Class nameAsserted necessary conditions Cerebellum Purkinje cell1.Is a ‘Neuron’ 2.Its soma lies within 'Purkinje cell layer of cerebellar cortex’ 3.It has ‘Projection neuron role’ 4.It uses ‘GABA’ as a neurotransmitter 5.It has ‘Spiny dendrite quality’ Class nameAsserted defining (necessary & sufficient) expression Cerebellum neuronIs a ‘Neuron’ whose soma lies in any part of the ‘Cerebellum’ or ‘Cerebellar cortex’ Principal neuronIs a ‘Neuron’ which has ‘Projection neuron role’, i.e., a neuron whose axon projects out of the brain region in which its soma lies GABAergic neuronIs a ‘Neuron’ that uses ‘GABA’ as a neurotransmitter O NTOLOGY – A SSERTED K NOWLEDGE 11NIF Standard Ontologies NIFSTD Ontologies neuinfo.org 11

N IF S TD C URRENT V ERSION 12NIF Standard Ontologies Key feature: Includes a set useful defined concepts to have inferred classifications of asserted concepts NIFSTD Ontologies neuinfo.org 12

NIFSTD B RIDGE F ILES NIF- Molecule NIF- Anatomy NIF-Cell NIF- Subcellular NIFSTD NIF-Neuron-BrainRegion-Bridge.owl Allows people to assert their own restrictions in a different bridge file without worrying about NIF-specific view of the restriction on core modules. Cross-module relations among classes are assigned in a separate bridging module. NIF-Neuron-NT-Bridge.owl Bridge NIFSTD Ontologies neuinfo.org 13

C ONCEPT -B ASED S EARCH Search Google: GABAergic neuron Search NIF: GABAergic neuron – NIF automatically searches for types of GABAergic neurons Types of GABAergic neurons NIFSTD Ontologies neuinfo.org 14

N IF S TD AND N EURO L EX W IKI Semantic wiki platform Provides simple forms for structured knowledge Can add concepts, properties Generate hierarchies without having to learn complicated ontology tools Good teaching tool for principles behind ontologies Community can contribute – Each term gets its own unique ID NIF Standard Ontologies 15 Stephen D. Larson et al. NIFSTD Ontologies neuinfo.org 15

A CCESS TO S HARED O NTOLOGIES NIFSTD is available as – OWL Format – RDF and SPARQL Endpoint Specific contents through web services – Available through NCBO Bioportal – Repository of biomedical ontologies – 199 ontologies including NIFSTD – Provides annotation and mapping services – INCF Program on Ontologies for Neural Structure – Neuronal Registry Task Force: Description of neural properties – Structural Lexicon: Description of structures across scales NIF Standard Ontologies16 NIFSTD Ontologies neuinfo.org 16

NIF Standard Ontologies17 DomainExternal Source Import/ Adapt NIFSTD Module Organism taxonomy NCBI Taxonomy, GBIF, ITIS, IMSR, Jackson Labs mouse catalog;. Specifically the taxonomy of model organisms in common use by neuroscientists AdaptNIF-Organism Molecules IUPHAR ion channels and receptors, Sequence Ontology (SO); pending: NCBI, NCBI Entrez Protein, NCBI RefSeq, NCBI Homologene; NIDA drug lists, ChEBI, and Protein Ontology (PRO) Adapt IUPHAR; import PRO NIF-Molecule NIF-Chemical Sub-cellular Sub-cellular AnatomyOntology (SAO). Extracted cell parts and subcellular structures from SAO-CORE. Soon to be importing GO Cellular Component with mapping ImportNIF-Subcellular Cell CCDB, NeuronDB, NeuroMorpho.org. terminologies; pending: OBO Cell Ontology AdaptNIF-Cell Gross Anatomy NeuroNames extended by including terms from BIRN, SumsDB, BrainMap.org, etc; Multi-scale representation of Nervous System Mac Macroscopic anatomy Adapt NIF- GrossAnatomy Nervous system function Sensory, Behavior, Cognition terms from NIF, BIRN, BrainMap.org, MeSH, and UMLS AdaptNIF-Function Nervous system dysfunction Nervous system disease from MeSH, NINDS terminology; pending: OMIMAdapt/Import NIF- Dysfunction Phenotypic qualities PATO Imported as part of the OBO foundry coreImportNIF-Quality Investigation: reagents Overlaps with molecules above, especially RefSeq for mRNA, ChEBI, Sequence ontology; pending: Protein Ontology import NIF- Investigation Investigation: instruments, protocols, plans Based on Ontology for Biomedical Investigation (OBI ) to include entities for biomaterial transformations, assays, data collection, data transformations. Adapt NIF- Investigation Investigation: resource type NIF, OBI, NITRC, Biomedical Resource Ontology (BRO)AdaptNIF-Resource Biological Process Gene Ontology’s (GO) biological process in wholeImportNIF- BioProcess NIFSTD EXTERNAL COMMUNITY SOURCES NIFSTD Ontologies neuinfo.org 17

So Far.. – Overlaps are detected and mappings were carefully curated – Included a bridging module that asserts equivalencies between NIF-Dysfunction and DOID We could MIREOT DOID Classes as well Drawback was loosing NIF’s annotation properties. Having the bridgeing module allowed us to have contents from both ontologies and to keep the mappings as well. (Did the same with NIF-Subcellular and GO-Cell Component) Collaborating on Mental Disorder - Addiction/ Substance related disorder with DOID group Taking a look at Barry Smith’s paper on Foundations for a realist ontology of mental disease NIF Standard Ontologies18 NIFSTD A ND DOID C OLLABORATION

W ORKING TO I NCORPORATE C OMMUNITY NeuroPsyGrid – NDAR Autism Ontology – Disease Phenotype Ontology – Cognitive Paradigm Ontology (CogPO) – Neural ElectroMagnetic Ontologies (NEMO) – 19NIF Standard Ontologies NIFSTD Ontologies neuinfo.org 19

S UMMARY AND C ONCLUSIONS NIF project with NIFSTD is an example of how ontologies can be used to enhance search and data integration across diverse resources NIFSTD continues to create an increasingly rich knowledgebase for neuroscience integrating with other life science community NIF encourages the use of community ontologies for resource providers 20NIF Standard Ontologies NIFSTD Ontologies neuinfo.org 20

Some questions: If someone asserts sameness should that be treated differently by others? – How would we know? Should there be a tool that would search these assertions? Can a lexicon be used as a set of base classes for use in ontology building? – We took this approach with nervous system cells by adding properties, then asserted hierarchies: GABAergic neuron Cerebellum neuron Intrinsic neuron NIFSTD Ontologies neuinfo.org 21

Even more questions? If a term has no definition, then should it exist in the lexicon? Do tests belong in ontologies? NIFSTD Ontologies neuinfo.org 22

NIFSTD Ontologies NeuroLex Wiki Neuroscience Information Framework (NIF) 23NIF Standard Ontologies NIFSTD Ontologies neuinfo.org 23