title: Automated extraction of information in molecular biology.
abstract: We review data mining techniques in molecular biology, specifically those that extract information from the scientific literature itself. As more of the biological literature is published electronically, there is an opportunity, and even a need, to automatically summarize the literature in a customized way, for example by associating keywords to a topic. These keywords can be extracted from relevant publications. The process of keyword extraction can be automated and optimized to keep literature pointers automatically up-to-date or to filter relevant information from the literature. To illustrate these points, OMIM (Online Mendelian Inheritance in Man), a database of human inherited diseases, was linked to the literature and keywords were derived that covered distinct aspects such as genetic information on the one hand and disease-specific protein and phenotypic information on the other. They were used to extract information that is helpful for keeping entries about disease up-to-date.
authors.affiliation: European Molecular Biology Laboratory, Meyerhofstr, 1, D-69012 Heidelberg, Germany.
authors.forename: M A
authors.initials: MA
authors.lastname: Andrade
authors.forename: P
authors.initials: P
authors.lastname: Bork
mesh_terms: D016208:Databases, Factual; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D006801:Humans; D008967:Molecular Biology / Q000379:methods*; D009862:Online Systems