- From: Helen Parkinson <parkinso@ebi.ac.uk>
- Date: Tue, 01 Sep 2009 20:10:52 +0100
- To: Nigam Shah <nigam@stanford.edu>
- CC: Kei Cheung <kei.cheung@yale.edu>, HCLS <public-semweb-lifesci@w3.org>, "tomasz.adamusiak@gmail.com" <tomasz.adamusiak@gmail.com>
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 19:11:46 UTC