PMID:17646304

Citation	Kim, JH, Mitchell, A, Attwood, TK and Hilario, M (2007) Learning to extract relations for protein annotation. Bioinformatics 23:i256-63
Abstract	Protein annotation is a task that describes protein X in terms of topic Y. Usually, this is constructed using information from the biomedical literature. Until now, most of literature-based protein annotation work has been done manually by human annotators. However, as the number of biomedical papers grows ever more rapidly, manual annotation becomes more difficult, and there is increasing need to automate the process. Recently, information extraction (IE) has been used to address this problem. Typically, IE requires pre-defined relations and hand-crafted IE rules or annotated corpora, and these requirements are difficult to satisfy in real-world scenarios such as in the biomedical domain. In this article, we describe an IE system that requires only sentences labelled according to their relevance or not to a given topic by domain experts.
Links	PubMed Online version:10.1093/bioinformatics/btm168
Keywords	Artificial Intelligence; Databases, Protein; Natural Language Processing; Pattern Recognition, Automated/methods; Periodicals as Topic; Proteins/chemistry; Proteins/classification; Sequence Analysis, Protein/methods
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