Download time awareness

Ontology based analyses methods ++
• develop a grammar for making productions using mf, bp, cl:
– derive a higher level grammar for next level of productions  derive
a formal annotation language?
• Add structure awareness: Create an iconic mapping for cl
terms to facilitate novel analyses.
• Add time awareness: express the temporal dimension and
have time-dependent annotations
GO based analysis of microarray data
TF-binding site & Annotation data
TF-sites show that the ABRE
and GBF sites are enriched
in these genes.
Component and function annotations show that these genes
are located in the chloroplast thylakoid membrane, are
part of the light-harvesting complex and have the molecular
function of chlorophyll binding and electron transport.
Clench is useful … but we need more!
• Clench helps the biologist interpret a list of genes
and form a result statement such as:
– The photosynthesis genes located in the chloroplast are
repressed in response to ozone stress and have the ABRE
binding site enriched in their promoters.
• More at www.personal.psu.edu/nhs109/Clench
Within-ontology “grammars”
OBOL
Relations Ontology
Between-ontology “grammars”
OBOL
OBOL
Relations Ontology
Relations Ontology
?<link>?
<Some MF> in <Some BP>
Payoff: If we have between-ontology grammars
• We can systematically store the interpretations (or
results) of GO based analyses
• We can browse [gene-expression] data in [particular
ontology] centric views
– Work of Gennari et al
• We can create semantically rich annotations that span
multiple ontologies.
Storing GO based analysis reports
The photosynthesis genes located in the
chloroplast are repressed in response to ozone
stress and have the ABRE binding site enriched in
their promoters.
The genes of the photosynthesis proteins
located in the chloroplast show a decrease in
their mRNA level in response to ozone stress
and have the ABRE binding site enriched in their
promoters.
Anatomy centric views by Gennari et al
• Established links between
the cellular structure terms
in FMA and the GO
cellular component terms
– Did it for 150 terms
• Established links between
tissue-region annotations
and brain anatomy terms in
FMA
Cyclin D1 is associated with cellular
proliferation in colon
Cyclin D1 is associated with
neuronal degeneration in brain
Cyclin D1 has <mf> in cellular
proliferation in colon
Semantically rich annotations
1. Relationship ontology
2. Mouse Pathology ontology
3. Tissue/Organ
4. Gene ontology
Basal layer of organ
shows membranous
staining
mRNA of genes encoding proteins
with mf in bp at cc is increased in
sample-id which shows some
pathology in some tissue in
some organ
Queries enabled:
1. Identify all images with a specific pathology
2. Identify cases with pathology and some gene expression changes
3. Correlate changes biological processes with change in morphology
Discovery enabled:
1. Classify samples in expression space and “look” for histological changes that
correlate with it.
HOW
WHY
Ontology based analyses methods ++
• develop a grammar for making productions using mf, bp, cl:
– derive a higher level grammar for next level of productions  derive
a formal Annotation language?
• Add structure awareness: Create an iconic mapping for cl
terms to facilitate novel analyses.
• Add time awareness: express the temporal dimension and
have time-dependent annotations
What about 3D structure of the cell?
Payoff: If we have iconic mappings
• We can browse ontologies in an anatomy centered manner
• Can use these new views for facilitating the annotation process
– i.e. improve curator  annotation tool interaction
• Create novel visualizations for interpreting high dimensional
datasets.
– Time course data [coming few slides later]
– Integrating gene expression, protein expression and metabolomic
datasets.
Ontology based analyses methods ++
• develop a grammar for making productions using mf, bp, cl:
– derive a higher level grammar for next level of productions  derive
a formal Annotation language?
• Add structure awareness: Create an iconic mapping for cl
terms to facilitate novel analyses.
• Add time awareness: express the temporal dimension and
have time-dependent annotations
What about the temporal dimension?
Overlay time course data
onto the GO tree.
See how the ‘enriched’
categories change over time.
Understand the dynamics of
the biological phenomenon
being studied.
–
Will complement
pathway based analysis
approaches
How about cell structure and time?