1. Neuroscience Information Framework Ontologies: Nerve cells in Neurolex and NIFSTD Maryann Martone University of California, San Diego

2. The Neuroscience Information Framework: Discovery and utilization of web-based resources for neuroscience http://neuinfo.org UCSD, Yale, Cal Tech, George Mason, Washington Univ Supported by NIH Blueprint  A portal for finding and using neuroscience resources  A consistent framework for describing resources  Provides simultaneous search of multiple types of information, organized by category  Supported by an expansive ontology for neuroscience  Utilizes advanced technologies to search the “hidden web”

3. Modular ontologies for neuroscience  NIF covers multiple structural scales and domains of relevance to neuroscience  Incorporated existing ontologies where possible; extending them for neuroscience where necessary  Normalized under the Basic Formal Ontology: an upper ontology used by the OBO Foundry  Single inheritance  Cross-domain relationships are being built in separate files NIFSTD NS Function MoleculeInvestigation Subcellular Anatomy Macromolecule Gene Molecule Descriptors Techniques ReagentProtocols Cell Instruments Bill Bug NS Dysfunction Quality Macroscopic Anatomy Organism Resource

4. Ontologies imported/used by NIF Gene Ontology Biological Process ChEBI (Mireot) PATO PRO (Bridge) BIRNLex OBI (Bridge) Disease Ontology (Mireot) Foundational Model of Anatomy (Mireot) Gene Ontology Cellular Component (Bridge) Neuronames, BAMS (Mapped) Cell Ontology (don’t use) Practical limitations imposed by tools and expertise; constantly addressing challenges involved in using community ontologies that are evolving in production information systems

5. NIF Cell Identity: Unique identifier nlx_neuron_nt_090803 http://ontology.neuinfo.org/NIF/BiomaterialEntities/NIF-Neuron-NT- Bridge.owl#nlx_neuron_nt_090803 http://ontology.neuinfo.org/NIF/BiomaterialEntities/NIF-Neuron-NT- Bridge.owl#nlx_neuron_nt_090803 Asserted hierarchy: Unique types of neuron Uniqueness assured by concatenating brain region with cell type Hippocampus CA1 pyramidal cell Neocortex layer 2/3 pyramidal cell Standard naming convention Major brain region, subregion, distinguishing characteristics, cell Bridge files: Cross module relations A set of properties that define it, e.g., part of, has neurotransmitter, has role Properties assigned at level of part of neuron where appropriate (brain region, molecule) Others at level of cell class: spiny, physiological Logical restrictions for defined classes: Necessary and sufficient conditions to identify members of that class GABAergic neuron is any member of class neuron has neurotransmitter GABA Gordon Shepherd, Giorgio Ascoli, Kei Cheung, Maryann Martone, Fahim Imam, Stephen Larson

6. Cerebellum Purkinje cell soma Cerebellum Purkinje cell dendrite Cerebellum Purkinje cell axon Cerebellum granule cell layer Cerebellum Purkinje cell layer Cerebellum molecular layer Has part Is part of Shared building blocks: Modular ontologies joined in bridge files Calbindin Cerebellum Purkinje neuron Cerebellar cortex Has part IP3 receptor NIF Molecule NIF Anatomy NIF Subcellular

7. Defined Classes Neuron by brain region NIF Cell, NIF Subcellular, NIF Anatomy Hippocampus neuron is a type of neuron has part soma is part of any part of hippocampus Neuron by molecule NIF Cell, NIF molecule Neurotransmitter GABAergic neuron By molecular constituent Parvalbumin-containing neuron Neuron by role Circuit role Principal neuron vs intrinsic neuron Functional role Sensory neuron, motor neuron Neuron by morphological quality Spiny neuron Pyramidal neuron Sometimes use OBO relations, sometimes short cuts that can be expressed in OBO relations

8. String vs concept based search

10. Currently ~250 proposed classes

11. Neuron qualities

12. What can account for signals here? Neurons are highly ramifying and polarized cells

13. Properties assigned at level of part of neuron

14. Community contributions: Neurolex Semantic Wiki Good teaching tool for the power of more formal semantics Knowledge base easier to view, index and navigate Lighter weight and more human friendly than more formal ontologies and tools Build knowledge from basic lexical elements and a few relationships Categories are linked through explicit properties Currently over 10,000 category pages Use relationship shortcuts that can be expressed in OBO relations Working with international group of neuroscientists to contribute content covering different domains and develop new content http://neurolex.org Stephen Larson and INCF

15. Detailed properties Custom form based interface Olfactory bulb (main) mitral cell New version just about to be released New version References for each attribute Meant to be used by anyone Curators (me) go through and translate Translated into NIFSTD once finalized Some short cut relations translated e.g., soma located in = neuron has part soma is part of some brain region

16. Inferring the Mesoscale The NIFSTD is expressed in OWL (Web Ontology Language) Supports reasoning and inference Through integration with other ontologies covering gross anatomy and molecular entities, we are working to create inferences across scales Analyze locally; infer globally If there’s an axon terminal, then there must be an axon… Stephen Larson

17. Desiderata 1000’s of neuron types; one group can’t do them all Early efforts all concentrate on same cell types (easy ones) INCF has opportunity to coordinate different groups so we can aggregate effort Standard set of properties and standard syntax for logical definitions Trying to base them on REL, but we take shortcuts for practical reasons Relation to GO function