RE: BioRDF Telcon

hi helen,

can you elaborate a bit more on this, i'm not sure exactly what you
mean.  what makes the overhead high and for who and what kind of errors
does the text mining produce?  what's the metric for performance?

cheers,
michael

Michael Miller
Lead Software Developer
Rosetta Biosoftware Business Unit
www.rosettabio.com

> -----Original Message-----
> From: public-semweb-lifesci-request@w3.org 
> [mailto:public-semweb-lifesci-request@w3.org] On Behalf Of 
> Helen Parkinson
> Sent: Tuesday, September 01, 2009 12:11 PM
> To: Nigam Shah
> Cc: Kei Cheung; HCLS; tomasz.adamusiak@gmail.com
> Subject: Re: BioRDF Telcon
> 
> NCI is a good match also for microarray data, but the 
> overhead of using 
> it is high, and more errors are generated when text mining 
> and through 
> user error. We get better performance from EFO than from NCIT.
> 
> best
> 
> Helen
> 
> Nigam Shah wrote:
> > On Tue, Sep 1, 2009 at 6:37 AM, Helen Parkinson 
> <parkinson@ebi.ac.uk 
> > <mailto:parkinson@ebi.ac.uk>> wrote:
> >
> >     The performance depends largely on how well the ontology is
> >     aligned with the input data, for this reason we 
> developed our own
> >     ontology. 
> >
> >
> > This is very true. However, if there is already an existing 
> ontology 
> > that matches the input data well (e.g. the NCI Thesaurus in case of 
> > Tissue Microarray Annotations in TMAD (http://tma.stanford.edu/) .. 
> > then its possible to use the annotator tool at NCBO 
> > (http://bioportal.bioontology.org/annotate).
> >
> > Regards,
> > Nigam. 
> 
> 

Received on Tuesday, 1 September 2009 20:09:00 UTC