A sentence sliding window approach to extract protein annotations from biomedical articles

Background: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been developed during the past years. Nevertheless, there is still a great ned of comparative assessment of the performance of the proposed methods and the development of common evaluation criteria. This issue was addressed by the Critical Assessment of Text Mining Methods in Molecular Biology (BioCreative) contest. The aim of this contest was to assess the performance of text mining systems applied to biomedical texts including tools which recognize named entities such as genes and proteins, and tools which automatically extract protein annotations. Results: The "sentence sliding window" approach proposed here was found to efficiently extract text fragments from full text articles containing annotations on proteins, providing the highest number of correctly predicted annotations. Moreover, the number of cor...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Martin Krallinger, Maria Padron, Alfonso Valencia
• Keywords: Annotation, BMCBI 2005, Proteins, Text Mining