- From: Kei Cheung <kei.cheung@yale.edu>
- Date: Thu, 11 Sep 2008 10:50:34 -0400
- To: Peter Ansell <ansell.peter@gmail.com>
- Cc: w3c semweb hcls <public-semweb-lifesci@w3.org>, eric neumann <ekneumann@gmail.com>
Peter Ansell wrote: > ----- "Kei Cheung" <kei.cheung@yale.edu> wrote: > > >> From: "Kei Cheung" <kei.cheung@yale.edu> >> To: "eric neumann" <ekneumann@gmail.com> >> Cc: "w3c semweb hcls" <public-semweb-lifesci@w3.org> >> Sent: Thursday, September 11, 2008 6:42:33 AM GMT +10:00 Brisbane >> Subject: Re: An application of the Semantic Web for finding alternative drug applications >> >> 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 >> > > What are the limits to what you can do with bare SPARQL in this area? Does it help to have elementary rdfs subclass knowledge for the topological parts? > > Cheers, > > Peter > > Hi Peter, When YeastHub [1] was being built, I was wondering whether Semantic Web (SW) technologies can help facilitate integrative biological network analysis including network topology. Later, a web-based tool called "tYNA" was created and published [2] which supports biological network analysis/visualization. tYNA was not implemented using SW, but I still wonder how some of its features can be implemented using SW. [1] http://bioinformatics.oxfordjournals.org/cgi/reprint/21/suppl_1/i85 [2] http://bioinformatics.oxfordjournals.org/cgi/content/full/22/23/2968 Cheers, -Kei
Received on Thursday, 11 September 2008 14:51:20 UTC