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.

DESCRIPTION:

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.

© 2011 Agarwal et al; licensee BioMed Central Ltd.