BioNOT: A searchable database of biomedical negated sentences.

Abstract

ABSTRACT: BACKGROUND: Negated biomedical events are often ignored by text-mining applications; however, such events carry scientific significance. We report on the development of BioNOT, a database of negated sentences that can be used to extract such negated events. Description: Currently BioNOT 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 BioNOT on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioNOT is able to capture negated events that may be ignored by experts. CONCLUSIONS: The BioNOT database can be a useful resource for biomedical researchers. BioNOT is freely available at http://bionot.askhermes.org/. In future work, we will develop semantic web related technologies to enrich BioNOT.