Re: An application of the Semantic Web for finding alternative drug applications

The following work seems to be a step towards extending SPARQL to 
include statistical mining capabilities:

http://www.ifi.uzh.ch/ddis/research/semweb/sparql-ml/

All these SPARQL extensions act as a bridge between semantic web and 
data mining.

-Kei

eric neumann wrote:

> Amit,
>
> There are a large class of data discovery problems that cannot be 
> solved via (SPARQL) query or even inferencing, simply because we don't 
> know what precise questions to ask in advance, though we may already 
> have enough evidence at hand (stored). 
>
> These kinds of problems (limited associative models) lend themselves 
> more to applications of large-scale statistical mining and bayesian 
> modeling... However, the latter tools are usually applied when one is 
> looking at 1-4 parameters at a time (e.g., incidence of a disease is 
> dependent on genetic factors, age, and diet). Now with 
> the possibility of having hundreds of such different attributes 
> available semantically, statistical approaches will have to be 
> augmented greatly. 
>
> SPARQL is an essential component for accessing/constraining SW data, 
> but by itself it is insufficient for the discovery of new associations 
> and mechanisms in whole biological systems. Many of the major 
> challenges within pharma R&D are precisely of this type!
>
> cheers,
> Eric
>
>
> On Thu, Sep 11, 2008 at 1:24 PM, Amit Sheth <amitpsheth@gmail.com 
> <mailto:amitpsheth@gmail.com>> wrote:
>
>     Finding "potentially interesting" paths, subgraphs, and pattering
>     in semantic web data (eg those
>     created from complex entity and relationship extraction from
>     biomedical literature [1],
>     semantic annotation and provenence of experimental data, and of
>     course structured datatabases) is
>     very useful in biomedical research
>     and requires SPARQL extensions. One of several examples along this
>     line is the
>     support for path queries as in SPARQ2L [2]. Other interesting
>     examples are
>     supporting spatio-temporal thematic queries and corresponding
>     extensions such as SPARQ-ST
>     [3] albeit we have not applied these extensions to sensor data so
>     far and not (yet) to biomedical domain.
>
>     Amit <http://knoesis.org/amit>
>
>     [1]
>     http://knoesis.wright.edu/research/semweb/projects/textMining/ekaw2008/
>     [2] http://knoesis.wright.edu/library/resource.php?id=00060
>     [3] http://knoesis.org/research/semweb/projects/stt/
>
>
>
>
>     On Thu, Sep 11, 2008 at 10:50 AM, Kei Cheung <kei.cheung@yale.edu
>     <mailto:kei.cheung@yale.edu>> wrote:
>
>
>         Peter Ansell wrote:
>
>             ----- "Kei Cheung" <kei.cheung@yale.edu
>             <mailto:kei.cheung@yale.edu>> wrote:
>
>              
>
>                 From: "Kei Cheung" <kei.cheung@yale.edu
>                 <mailto:kei.cheung@yale.edu>>
>                 To: "eric neumann" <ekneumann@gmail.com
>                 <mailto:ekneumann@gmail.com>>
>                 Cc: "w3c semweb hcls" <public-semweb-lifesci@w3.org
>                 <mailto: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
>
>
>
>
>
>
>     -- 
>     Amit Sheth http://knoesis.org
>
>

Received on Friday, 12 September 2008 01:50:46 UTC