title: Opportunities for text mining in the FlyBase genetic literature curation workflow.
abstract: FlyBase is the model organism database for Drosophila genetic and genomic information. Over the last 20 years, FlyBase has had to adapt and change to keep abreast of advances in biology and database design. We are continually looking for ways to improve curation efficiency and efficacy. Genetic literature curation focuses on the extraction of genetic entities (e.g. genes, mutant alleles, transgenic constructs) and their associated phenotypes and Gene Ontology terms from the published literature. Over 2000 Drosophila research articles are now published every year. These articles are becoming ever more data-rich and there is a growing need for text mining to shoulder some of the burden of paper triage and data extraction. In this article, we describe our curation workflow, along with some of the problems and bottlenecks therein, and highlight the opportunities for text mining. We do so in the hope of encouraging the BioCreative community to help us to develop effective methods to mine this torrent of information. DATABASE URL: http://flybase.org
authors.affiliation: Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK. p.mcquilton@gen.cam.ac.uk
authors.forename: Peter
authors.initials: P
authors.lastname: McQuilton
mesh_terms: D000818:Animals; D057225:Data Mining / Q000379:methods*; D030541:Databases, Genetic; D004330:Drosophila / Q000235:genetics*; D010641:Phenotype; D057188:Workflow