BioNØT: a searchable database of biomedical negated sentences.
BACKGROUND
Negated biomedical events are often ignored by text-mining applications; however, such events carry scientific significance. We report on the development of BioNØT, a database of negated sentences that can be used to extract such negated events.


METHODS
Currently BioNØT incorporates ≈32 million negated sentences, extracted from over 336 million biomedical sentences from three resources: ≈2 million full-text biomedical articles in Elsevier and the PubMed Central, as well as ≈20 million abstracts in PubMed. We evaluated BioNØT on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioNØT is able to capture negated events that may be ignored by experts.


CONCLUSIONS
The BioNØT database can be a useful resource for biomedical researchers. BioNØT is freely available at http://bionot.askhermes.org/. In future work, we will develop semantic web related technologies to enrich BioNØT.
Medical Informatics, College of Engineering and Applied Sciences, University of Wisconsin-Milwaukee, 3200 N, Cramer St, Milwaukee, WI 53201-0784, USA.
Shashank
S
Agarwal
Hong
H
Yu
Issac
I
Kohane
D000465:Algorithms; D000544:Alzheimer Disease / Q000235:genetics; D001321:Autistic Disorder / Q000235:genetics; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D020407:Internet; D010300:Parkinson Disease / Q000235:genetics; D039781:PubMed