title: PathNER: a tool for systematic identification of biological pathway mentions in the literature.
abstract: BACKGROUND
  Biological pathways are central to many biomedical studies and are frequently discussed in the literature. Several curated databases have been established to collate the knowledge of molecular processes constituting pathways. Yet, there has been little focus on enabling systematic detection of pathway mentions in the literature.
  
  
  RESULTS
  We developed a tool, named PathNER (Pathway Named Entity Recognition), for the systematic identification of pathway mentions in the literature. PathNER is based on soft dictionary matching and rules, with the dictionary generated from public pathway databases. The rules utilise general pathway-specific keywords, syntactic information and gene/protein mentions. Detection results from both components are merged. On a gold-standard corpus, PathNER achieved an F1-score of 84%. To illustrate its potential, we applied PathNER on a collection of articles related to Alzheimer's disease to identify associated pathways, highlighting cases that can complement an existing manually curated knowledgebase.
  
  
  CONCLUSIONS
  In contrast to existing text-mining efforts that target the automatic reconstruction of pathway details from molecular interactions mentioned in the literature, PathNER focuses on identifying specific named pathway mentions. These mentions can be used to support large-scale curation and pathway-related systems biology applications, as demonstrated in the example of Alzheimer's disease. PathNER is implemented in Java and made freely available online at http://sourceforge.net/projects/pathner/.
authors.forename: Chengkun
authors.initials: C
authors.lastname: Wu
authors.forename: Jean-Marc
authors.initials: JM
authors.lastname: Schwartz
authors.forename: Goran
authors.initials: G
authors.lastname: Nenadic
mesh_terms: D000544:Alzheimer Disease / Q000378:metabolism; D057225:Data Mining / Q000379:methods*; D015398:Signal Transduction; D049490:Systems Biology / Q000379:methods*