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We present a classifier system called SRPFP that predicts the functions of un-annotated proteins. SRPFP aims at enhancing the state of the art of biological text mining. It analyzes biomedical texts in order to discover protein function information that is difficult to retrieve. It employs semantic rules for extracting proteins functions information from biomedical abstracts. It applies a novel model...
We present a Natural Language Processing extraction system called IESforPFP, which can retrieve useful information from biomedical abstracts. IESforPFP aims at enhancing the state of the art of biological text mining by applying novel linguistic computational technique. By retrieving significant patterns of associations between proteins and molecules from biomedical abstracts, IESforPFP can determine...
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