title: GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles.
abstract: Systems that extract structured information from natural language passages have been highly successful in specialized domains. The time is opportune for developing analogous applications for molecular biology and genomics. We present a system, GENIES, that extracts and structures information about cellular pathways from the biological literature in accordance with a knowledge model that we developed earlier. We implemented GENIES by modifying an existing medical natural language processing system, MedLEE, and performed a preliminary evaluation study. Our results demonstrate the value of the underlying techniques for the purpose of acquiring valuable knowledge from biological journals.
authors.affiliation: Computer Science Dept, Queens College CUNY, Flushing, NY, 11367, USA. friedman.carol@dmi.columbia.edu
authors.forename: C
authors.initials: C
authors.lastname: Friedman
authors.forename: P
authors.initials: P
authors.lastname: Kra
authors.forename: H
authors.initials: H
authors.lastname: Yu
authors.forename: M
authors.initials: M
authors.lastname: Krauthammer
authors.forename: A
authors.initials: A
authors.lastname: Rzhetsky
mesh_terms: D001185:Artificial Intelligence; D019295:Computational Biology; D008967:Molecular Biology; D009323:Natural Language Processing; D010506:Periodicals as Topic; D010865:Pilot Projects