title: Annotating genes and genomes with DNA sequences extracted from biomedical articles.
abstract: BACKGROUND
  Increasing rates of publication and DNA sequencing make the problem of finding relevant articles for a particular gene or genomic region more challenging than ever. Existing text-mining approaches focus on finding gene names or identifiers in English text. These are often not unique and do not identify the exact genomic location of a study.
  
  
  RESULTS
  Here, we report the results of a novel text-mining approach that extracts DNA sequences from biomedical articles and automatically maps them to genomic databases. We find that ∼20% of open access articles in PubMed central (PMC) have extractable DNA sequences that can be accurately mapped to the correct gene (91%) and genome (96%). We illustrate the utility of data extracted by text2genome from more than 150 000 PMC articles for the interpretation of ChIP-seq data and the design of quantitative reverse transcriptase (RT)-PCR experiments.
  
  
  CONCLUSIONS
  Our approach links articles to genes and organisms without relying on gene names or identifiers. It also produces genome annotation tracks of the biomedical literature, thereby allowing researchers to use the power of modern genome browsers to access and analyze publications in the context of genomic data.
  
  
  METHODS
  Source code is available under a BSD license from http://sourceforge.net/projects/text2genome/ and results can be browsed and downloaded at http://text2genome.org.
authors.affiliation: Faculty of Life Sciences, University of Manchester, Manchester, UK. maximilianh@gmail.com
authors.forename: Maximilian
authors.initials: M
authors.lastname: Haeussler
authors.forename: Martin
authors.initials: M
authors.lastname: Gerner
authors.forename: Casey M
authors.initials: CM
authors.lastname: Bergman
mesh_terms: D001483:Base Sequence; D047369:Chromatin Immunoprecipitation; D004247:DNA / Q000737:chemistry*; D057225:Data Mining / Q000379:methods*; D030561:Databases, Nucleic Acid; D005796:Genes; D016678:Genome; D058977:Molecular Sequence Annotation; D039781:PubMed; D020133:Reverse Transcriptase Polymerase Chain Reaction; D017422:Sequence Analysis, DNA; D012984:Software
chemical_list: D004247:DNA