title: NLP-based information extraction for managing the molecular biology literature.
abstract: We present research aimed at devising a tool for using natural language processing to identify and extract biomedical information from text for the purpose of assisting researchers in molecular biology manage large amounts of information. A pilot project based on the molecular genetics of diabetes demonstrates our ability to explore the interaction of genomic phenomena and clinical findings. We suggest the cooperation of this extracted information with systems for clustering text and constructing labeled networks of data.
authors.affiliation: University of North Carolina, Chapel Hill, NC, USA.
authors.forename: Bisharah
authors.initials: B
authors.lastname: Libbus
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Rindflesch
mesh_terms: D003920:Diabetes Mellitus / Q000235:genetics*; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008967:Molecular Biology; D009323:Natural Language Processing; D010865:Pilot Projects