The document discusses neuroscience ontologies created by the Neuroscience Information Framework (NIF). It describes how NIF incorporates existing ontologies and extends them for neuroscience as needed. NIF includes modular ontologies covering multiple scales including molecules, cells, anatomy, and functions. Key ontologies discussed include NIFSTD, Neurolex, and bridging files that link related concepts across ontologies. Examples are provided of how neuron classes are defined based on attributes such as brain region, molecular constituents, and roles.
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
Molecule Investigation
Subcellular
Anatomy
Macromolecule Gene
Molecule
Descriptors
Techniques
Reagent Protocols
Cell
Instruments
Bill Bug
NS
Dysfunction
Quality
Macroscopic
AnatomyOrganism
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
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
Has
part
Has
part
Is part of
Is part of
Is part of
Shared building blocks: Modular ontologies
joined in bridge files
Calbindin
Cerebellum
Purkinje neuron
Cerebellar cortex
Has part
Has part
Has part
IP3
receptor
NIF Molecule
NIF Anatomy
NIF Subcellular
7. DefinedClasses
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
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
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