BioNempty setT: 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 BioNempty setT, a database of negated sentences that can be used to extract such negated events. Description: Currently BioNempty setT incorporates approximate to 32 million negated sentences, extracted from over 336 million biomedical sentences from three resources: approximate to 2 million full-text biomedical articles in Elsevier and the PubMed Central, as well as approximate to 20 million abstracts in PubMed. We evaluated BioNempty setT on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioNempty setT is able to capture negated events that may be ignored by experts. Conclusions: The BioNempty setT database can be a useful resource for biomedical researchers. BioNempty setT is freely available at http://bionot.askhermes.org/. In future work, we will develop semantic web related technologies to enrich BioNempty setT.