title: Classification and prioritization of biomedical literature for the comparative toxicogenomics database.
abstract: We present a new approach to perform biomedical documents classification and prioritization for the Comparative Toxicogenomics Database (CTD). This approach is motivated by needs such as literature curation, in particular applied to the human health environment domain. The unique integration of chemical, genes/proteins and disease data in the biomedical literature may advance the identification of exposure and disease biomarkers, mechanisms of chemical actions, and the complex aetiologies of chronic diseases. Our approach aims to assist biomedical researchers when searching for relevant articles for CTD. The task is functionally defined as a binary classification task, where selected articles must also be ranked by order of relevance. We design a SVM classifier, which combines three main feature sets: an information retrieval system (EAGLi), a biomedical named-entity recognizer (MeSH term extraction), a gene normalization (GN) service (NormaGene) and an ad-hoc keyword recognizer for diseases and chemicals. The evaluation of the gene identification module was done on BioCreativeIII test data. Disease normalization is achieved with 95% precision and 93% of recall. The evaluation of the classification was done on the corpus provided by BioCreative organizers in 2012. The approach showed promising performance on the test data.
authors.affiliation: University Hospitals of Geneva, Geneva, Switzerland. dina.vishnyakova@hcuge.ch
authors.forename: Dina
authors.initials: D
authors.lastname: Vishnyakova
authors.forename: Emilie
authors.initials: E
authors.lastname: Pasche
authors.forename: Julien
authors.initials: J
authors.lastname: Gobeill
authors.forename: Arnaud
authors.initials: A
authors.lastname: Gaudinat
authors.forename: Christian
authors.initials: C
authors.lastname: Lovis
authors.forename: Patrick
authors.initials: P
authors.lastname: Ruch
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D062126:Databases, Chemical; D030541:Databases, Genetic; D064420:Drug-Related Side Effects and Adverse Reactions / Q000145:classification*; D006801:Humans; D010506:Periodicals as Topic / Q000145:classification*; D043922:Toxicogenetics / Q000379:methods*; D014584:User-Computer Interface