This is wonderful, Matthias.
We need to look at how this jibes with what we've created in BIRN &
NIF for the IUPHAR classification for G-protein coupled receptors.
We definitely want our representations to stay commensurate. We've
got this in the ontology driving integration between SenseLab, CCDB,
and NeuroMorpho.org. This includes the complete set of NeuroName
brain regions refactored for a BFO+OBO-RO + PATO representation in
OWL (BIRNLex-Anatomy), nerve cell types (NIF-Cell.owl) which we are
working to make compatible with the OBO CL ontology, and OBI.
For the IUPHAR representation, I'm using the Sequence ontology, BFO,
OBO-RO, and PATO. I also use NCBI eUtils to draw out multiple
organism representations using Homologene, as well as to assemble all
the appropriate parts from protein superfamily to the organism-
specific protein (think UniProt) on through to transcript, gene, and
chromosome, so that you could resolve a SPARQL query that asks:
What Cav2-type Ca++-Channels are on mouse chromosome 11?
I've got ligands in there - at least those the IUPHAR group has
listed for the receptor families. It's nothing like the variety in
PSPD Ki (7500 test ligands). There are some blank node problems with
my current representation of the ligand interactions that I have to
fix, but it does use the BFO dependent continuants to describe a
"disposition to bind" a ligand which is then linked to specific
ligands (e.g., the many Adenosine analogs that bind to the various
Adenosine receptors). I'm not certain whether disposition is the way
to do this - or whether there should be a "ligand role" that inheres
in the ligand molecules. You're still left trying to figure out how
to link the ligands to the receptors. The alternative is to
represent the binding process - which you are doing very nicely here
using the generic GO "binding" molecular function. Since IUPHAR is
receptor-centric, representing binding as a disposition of the
receptors, seemed reasonable as a first pass on IUPHAR.
The other issue I've still not worked out is in order to be able to
infer the set described in the example above, all the classes need to
have the proper disjoint relations and closing axioms. I can easily
do this, since this whole representation is algorithmically generated
off an algorithmic dump of the IUPHAR spreadsheets using Jena & the
NCBI eUtils. The problem was, when I put the sibling disjoints in
there for the mRNAs & genes (essentially 500+ sibling descendants of
SO:mRNA and SO:multi-cistronic gene), I couldn't open the file in
Protege v3.3.1, so I had to drop those for the time being.
One comment on the PSPD Ki representation you have:
Do you have the tissue & organism source fields from PSPD Ki? If
these could be included in the result list (maybe even used to sort
the list - in addition to sorting on ligand), then it would be clear
why there are multiple entries for some of the ligands.
Again - very nice work.
Cheers,
Bill
P.S.: We've also run the same conversion on the IUPHAR voltage-gated
ion channels. Both of these will be reviewed at the upcoming Protege
Ontology (PRO) meeting to figure out how to make use of Sequence
Ontology & the PRO components (ProEvo & ProForm) - as well as the RNA
Ontology.
As I mentioned about 2 months ago, these files are available for
review at:
BIRNLex ontology (some components re-used in NIF ontology):
http://purl.org/nbirn/birnlex/ontology/birnlex.owl
NIF ontology:
http://purl.org/nif/ontology/nif.owl
On Oct 31, 2007, at 11:10 AM, [EMAIL PROTECTED] wrote:
I have uploaded the 'beta version' of the OWL conversion of the
PDSP Ki database to the SPARQL endpoint hosted by DERI.
The address is:
http://hcls.deri.ie/sparql
Alternatively, you can also use the SPARQL endpoint of the Yale
Center for Medical Informatics (only contains the SenseLab
ontologies):
http://neuroweb.med.yale.edu:8890/sparql
Since the datasets makes use of the SenseLab URIs for receptors,
the queries can also be connected to further information about
neuronal cell types, cellular properties, brain regions etc.
A possible SPARQL query showing some ligands of the serotonin
receptor 5-HT2A, together with their affinity (lower values mean
higher affinity, i.e. the substance is of higher pharmacological
interest):
=====
PREFIX neurondb: <http://purl.org/ycmi/senselab/neuron_ontology.owl#>
PREFIX obo_essentials: <http://purl.org/zen/obo_essentials.owl#>
PREFIX ro:
<http://www.obofoundry.org/ro/ro.owl#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?name_of_ligand ?ki_value FROM <http://purl.org/ycmi/ki/
core.owl> WHERE {?nicotinic_receptor a neurondb:_5-HT2A .
?ligand a ?ligand_class .
?process a obo_essentials:GO_0005488_process .
?process ro:has_participant ?nicotinic_receptor .
?process ro:has_participant ?ligand .
?ligand_class rdfs:label ?name_of_ligand .
?ligand ro:bearer_of ?quality .
?quality rdf:value ?ki_value .
}
=====
First three results:
name_of_ligand -- ki_value
--------------------------
tryptamine -- 218.7761623949
(R)-noradrenaline --455970.15
yohimbine -- 4790
chlorpromazine -- 1.8
Some of the ligands have the name 'null', this still needs to be
fixed.
The PDSP Ki datasets can be mirrored on other installations of
Virtuoso with the following iSQL command:
DB.DBA.RDF_LOAD_RDFXML(
xml_uri_get('http://neuroweb.med.yale.edu/svn/trunk/ontology/ki/
core.owl', 'http://neuroweb.med.yale.edu/svn/trunk/ontology/ki/
core.owl'),
'http://purl.org/ycmi/ki/core.owl', 'http://purl.org/ycmi/ki/core.owl'
)
Please note that the current HCLS demo knowledge base contains
outdated namespaces for the SenseLab ontologies (we are using PURLs
now), so the PDSP Ki datasets do not readily connect to the rest of
the knowledge base. The namespaces in the demo KB will soon be
updated (at least I would like to do so).
cheers,
Matthias Samwald
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William Bug, M.S., M.Phil.
email: [EMAIL PROTECTED]
Ontological Engineer/Programmer Analyst III work: (858) 822-0739
Biomedical Informatics Research Network
Dept. of Neuroscience, School of Medicine
University of California, San Diego
9500 Gilman Drive
La Jolla, CA 92093
Please note my email has recently changed
