title: PathBinder--text empirics and automatic extraction of biomolecular interactions.
abstract: BACKGROUND
  The increasingly large amount of free, online biological text makes automatic interaction extraction correspondingly attractive. Machine learning is one strategy that works by uncovering and using useful properties that are implicit in the text. However these properties are usually not reported in the literature explicitly. By investigating specific properties of biological text passages in this paper, we aim to facilitate an alternative strategy, the use of text empirics, to support mining of biomedical texts for biomolecular interactions. We report on our application of this approach, and also report some empirical findings about an important class of passages. These may be useful to others who may also wish to use the empirical properties we describe.
  
  
  RESULTS
  We manually analyzed syntactic and semantic properties of sentences likely to describe interactions between biomolecules. The resulting empirical data were used to design an algorithm for the PathBinder system to extract biomolecular interactions from texts. PathBinder searches PubMed for sentences describing interactions between two given biomolecules. PathBinder then uses probabilistic methods to combine evidence from multiple relevant sentences in PubMed to assess the relative likelihood of interaction between two arbitrary biomolecules. A biomolecular interaction network was constructed based on those likelihoods.
  
  
  CONCLUSIONS
  The text empirics approach used here supports computationally friendly, performance competitive, automatic extraction of biomolecular interactions from texts.
  
  
  BACKGROUND
  http://www.metnetdb.org/pathbinder.
authors.affiliation: Iowa State University, Ames, Iowa, USA.
authors.forename: Lifeng
authors.initials: L
authors.lastname: Zhang
authors.forename: Daniel
authors.initials: D
authors.lastname: Berleant
authors.forename: Jing
authors.initials: J
authors.lastname: Ding
authors.forename: Tuan
authors.initials: T
authors.lastname: Cao
authors.forename: Eve
authors.initials: E
authors.lastname: Syrkin Wurtele
mesh_terms: D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D003628:Database Management Systems; D039781:PubMed; D012984:Software