tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles.
The breadth and depth of biomedical literature are increasing year upon year. To keep abreast of these increases, FlyBase, a database for Drosophila genomic and genetic information, is constantly exploring new ways to mine the published literature to increase the efficiency and accuracy of manual curation and to automate some aspects, such as triaging and entity extraction. Toward this end, we present the 'tagtog' system, a web-based annotation framework that can be used to mark up biological entities (such as genes) and concepts (such as Gene Ontology terms) in full-text articles. tagtog leverages manual user annotation in combination with automatic machine-learned annotation to provide accurate identification of gene symbols and gene names. As part of the BioCreative IV Interactive Annotation Task, FlyBase has used tagtog to identify and extract mentions of Drosophila melanogaster gene symbols and names in full-text biomedical articles from the PLOS stable of journals. We show here the results of three experiments with different sized corpora and assess gene recognition performance and curation speed. We conclude that tagtog-named entity recognition improves with a larger corpus and that tagtog-assisted curation is quicker than manual curation. DATABASE URL: www.tagtog.net, www.flybase.org.
Goerresstr. 20, Munich 80798, Germany, Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK, Department of Informatics, Technical University of Munich (TUM), Garching 85748, Germany.
Juan Miguel
JM
Cejuela
Peter
P
McQuilton
Laura
L
Ponting
Steven J
SJ
Marygold
Raymund
R
Stefancsik
Gillian H
GH
Millburn
Burkhard
B
Rost
D000818:Animals; D057225:Data Mining / Q000379:methods*; D004330:Drosophila / Q000235:genetics; D020407:Internet; D058977:Molecular Sequence Annotation / Q000379:methods*; D012984:Software; D014584:User-Computer Interface; D018875:Vocabulary, Controlled