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Open Access Highly Accessed Database

BioN∅T: A searchable database of biomedical negated sentences

Shashank Agarwal1, Hong Yu123* and Issac Kohane4

Author Affiliations

1 Medical Informatics, College of Engineering and Applied Sciences, University of Wisconsin-Milwaukee, 3200 N. Cramer St., Milwaukee WI 53201-0784, USA

2 Department of Computer Science and Electrical Engineering, College of Engineering and Applied Sciences, University of Wisconsin-Milwaukee, 3200 N. Cramer St., Milwaukee WI 53201-0784, USA

3 Department of Health Sciences, College of Health Science, University of Wisconsin-Milwaukee, 2400 E. Hartford Ave., Milwaukee WI 53211, USA

4 Children's Hospital Informatics Program, Children's Hospital, 300 Longwood Ave., Enders-6, Boston MA 02115, USA

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BMC Bioinformatics 2011, 12:420  doi:10.1186/1471-2105-12-420

Published: 27 October 2011

Abstract

Background

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

Description

Currently BioN∅T 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 BioN∅T on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioN∅T is able to capture negated events that may be ignored by experts.

Conclusions

The BioN∅T database can be a useful resource for biomedical researchers. BioN∅T is freely available at http://bionot.askhermes.org/. webcite In future work, we will develop semantic web related technologies to enrich BioN∅T.