November 20, 2009 1 Comment
(Notes frm the presentation as it happens)
Knowledge is not uni or bivariate, but we think of it as such: this leads to information loss.
Naming things: showing example of a trivial name, an IUPAC systematic name and an InChI and points out that these have different information content.
Points out scaling problem: drug discovery is multivariate and happens in a space of approx 1016 molecules (all molecules that are feasible and thought to be drug-like). Information loss occurs as you traverse this space backwards and forwards.
Now talks about molecular information in RDF: http://rdf.openmolecules.net for the provision of derefernceable URIs for molecules….and plugging the Chemistry Development Kit (CDK) as a means for cnverting between multiple representations of a molecule. Now moves on to Bioclipse as an integrating tool that allows chemical data transformations and the tracking of vwhy these transformations occur (version-controllable scripts to drive Bioclipse).
RDF extension to bioclipse: local RDF storage, read/write RDF, run SPARQL queries and extract RDF from XHTTML/RDFa.
Now shows an example of the expression of the CDK data model using ontologies but no details. Brief mention of his recent descriptor ontology.