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• W2117243442 abstract "Abstract Motivation: New high-throughput technologies have accelerated the accumulation of knowledge about genes and proteins. However, much knowledge is still stored as written natural language text. Therefore, we have developed a new method, GAPSCORE, to identify gene and protein names in text. GAPSCORE scores words based on a statistical model of gene names that quantifies their appearance, morphology and context. Results: We evaluated GAPSCORE against the Yapex data set and achieved an F-score of 82.5% (83.3% recall, 81.5% precision) for partial matches and 57.6% (58.5% recall, 56.7% precision) for exact matches. Since the method is statistical, users can choose score cutoffs that adjust the performance according to their needs. Availability: GAPSCORE is available at http://bionlp.stanford.edu/gapscore/" @default.
• W2117243442 created "2016-06-24" @default.
• W2117243442 creator A5004242684 @default.
• W2117243442 creator A5071144367 @default.
• W2117243442 creator A5084043782 @default.
• W2117243442 date "2004-01-22" @default.
• W2117243442 modified "2023-10-14" @default.
• W2117243442 title "GAPSCORE: finding gene and protein names one word at a time" @default.
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• W2117243442 doi "https://doi.org/10.1093/bioinformatics/btg393" @default.
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• W2117243442 hasPublicationYear "2004" @default.
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