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MOTIVATION Protein-protein interactions play critical roles in biological processes, and many biologists try to find or to predict crucial information concerning these interactions. Before verifying interactions in biological laboratory work, validating them from previous research is necessary. Although many efforts have been made to create databases that(More)
As the number of biological literatures grows exponentially, needs for text mining system are increased. In text mining area, normalization is mapping gene/protein names to a database. It is necessary to combine extracted information from various literatures and to curate a database or an ontology using literatures. Previous normalization researches used(More)
The numbers of articles and journals that are published are increasing at a considerable rate, and the published information is growing continuously and fast. Because of this, researches to acquire knowledge automatically have been carried out in the areas of information retrieval, information extraction and text mining. Information retrieval approaches are(More)
According to the explosion of online biomedical texts, it becomes more difficult to get exact information manually. The named entity recognition is the very first step for further text mining tasks like information extraction, knowledge discovery and others. In this paper, we present our statistical named entity recognition method. Until now, there were(More)
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