Thanks for sharing the papers, Eric. I went through some of the papers
including the one you mentioned (interestingly there is a paper on
wiki). I think they're interesting. They reminded me of "mining for the
semantic web" (ontology learning?) and "mining from the semantic web"
(data mining). For biological networks, we need to do both semantic and
topological queries. It might be difficult to achieve the latter using
SPARQL (e.g., finding protein hubs). Maybe we need some extensions of
SPARQL.
Best,
-Kei
eric neumann wrote:
Below is the reference and link to the paper (presented at
Bio-Ontologies, ISMB 2008) I mentioned during last week's HCLS call...
Angela X. Qu et al.
"Tamoxifen to Systemic Lupus Erythematosus:Constructing a Semantic
Infrastructure to Enable Mechanism-based Reasoning andInference from
Drugs to Diseases"
The paper can be found along with others
in http://www.bio-ontologies.org.uk/download/Bio-Ontologies2008.pdf
What I think is worth noting in this paper, is that in addition to
SPARQL-endpoints and ontologies, there are additional ways of finding
patterns and mining information from RDF structures based on
graph-theoretic methods.
Eric
