Genome biology · 2008 · 490 citations · 29 references
ComputingBioinformaticsComputer ScienceBiomedical Text MiningInformation RetrievalNatural Language ProcessingGene Mention DetectionGenomic AnnotationNamed Entity RecognitionSequence AnnotationSequence LabelingGene Entity RecognitionGene Mention AnnotationGene Mention Evaluation MetricsGene Name DisambiguationGene Name Entity RecognitionGene Name Tagging
Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all the methods used and a statistical analysis of the results. We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions.
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