title: Harmonization of gene/protein annotations: towards a gold standard MEDLINE.
abstract: BACKGROUND
  The recognition of named entities (NER) is an elementary task in biomedical text mining. A number of NER solutions have been proposed in recent years, taking advantage of available annotated corpora, terminological resources and machine-learning techniques. Currently, the best performing solutions combine the outputs from selected annotation solutions measured against a single corpus. However, little effort has been spent on a systematic analysis of methods harmonizing the annotation results and measuring against a combination of Gold Standard Corpora (GSCs).
  
  
  RESULTS
  We present Totum, a machine learning solution that harmonizes gene/protein annotations provided by heterogeneous NER solutions. It has been optimized and measured against a combination of manually curated GSCs. The performed experiments show that our approach improves the F-measure of state-of-the-art solutions by up to 10% (achieving ≈70%) in exact alignment and 22% (achieving ≈82%) in nested alignment. We demonstrate that our solution delivers reliable annotation results across the GSCs and it is an important contribution towards a homogeneous annotation of MEDLINE abstracts.
  
  
  METHODS
  Totum is implemented in Java and its resources are available at http://bioinformatics.ua.pt/totum
authors.affiliation: University of Aveiro, IEETA/DETI, Campus Universitário de Santiago, Aveiro, Portugal. david.campos@ua.pt
authors.forename: David
authors.initials: D
authors.lastname: Campos
authors.forename: Sérgio
authors.initials: S
authors.lastname: Matos
authors.forename: Ian
authors.initials: I
authors.lastname: Lewin
authors.forename: José Luís
authors.initials: JL
authors.lastname: Oliveira
authors.forename: Dietrich
authors.initials: D
authors.lastname: Rebholz-Schuhmann
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D057225:Data Mining; D006801:Humans; D016239:MEDLINE; D051379:Mice; D058977:Molecular Sequence Annotation / Q000592:standards; D011506:Proteins / Q000235:genetics*; D009626:Terminology as Topic; D014481:United States
chemical_list: D011506:Proteins