- From: Kei Cheung <kei.cheung@yale.edu>
- Date: Wed, 10 Sep 2008 16:42:33 -0400
- To: eric neumann <ekneumann@gmail.com>
- CC: w3c semweb hcls <public-semweb-lifesci@w3.org>
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 > >
Received on Wednesday, 10 September 2008 20:43:23 UTC