title: Sifting abstracts from Medline and evaluating their relevance to molecular biology.
abstract: The most important knowledge in the area of biology currently consists of raw text documents. Bibliographic databases of biomedical articles can be searched, but an efficient procedure should evaluate the relevance of documents to biology. In genetics, this challenge is even trickier, because of the lack of consistency in genes' naming tradition. We aim to define a good approach for collecting relevant abstracts for biology and for studied species and genes. Our approach relies on defining best queries, detecting and filtering best sources.
authors.affiliation: Université Paris Descartes, Faculté de Médecine, Inserm, U729, SPIM, 75006 Paris, France. natalia.grabar@spim.jussieu.fr
authors.forename: Natalia
authors.initials: N
authors.lastname: Grabar
authors.forename: Marie-Christine
authors.initials: MC
authors.lastname: Jaulent
authors.forename: Antoine
authors.initials: A
authors.lastname: Chambaz
authors.forename: Céline
authors.initials: C
authors.lastname: Lefebvre
authors.forename: Christian
authors.initials: C
authors.lastname: Néri
mesh_terms: D005602:France; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D008967:Molecular Biology; D009323:Natural Language Processing