title: A SNPshot of PubMed to associate genetic variants with drugs, diseases, and adverse reactions.
abstract: BACKGROUND
  Genetic factors determine differences in pharmacokinetics, drug efficacy, and drug responses between individuals and sub-populations. Wrong dosages of drugs can lead to severe adverse drug reactions in individuals whose drug metabolism drastically differs from the "assumed average". Databases such as PharmGKB are excellent sources of pharmacogenetic information on enzymes, genetic variants, and drug response affected by changes in enzymatic activity. Here, we seek to aid researchers, database curators, and clinicians in their search for relevant information by automatically extracting these data from literature.
  
  
  METHODS
  We automatically populate a repository of information on genetic variants, relations to drugs, occurrence in sub-populations, and associations with disease. We mine textual data from PubMed abstracts to discover such genotype-phenotype associations, focusing on SNPs that can be associated with variations in drug response. The overall repository covers relations found between genes, variants, alleles, drugs, diseases, adverse drug reactions, populations, and allele frequencies. We cross-reference these data to EntrezGene, PharmGKB, PubChem, and others.
  
  
  RESULTS
  The performance regarding entity recognition and relation extraction yields a precision of 90-92% for the major entity types (gene, drug, disease), and 76-84% for relations involving these types. Comparison of our repository to PharmGKB reveals a coverage of 93% of gene-drug associations in PharmGKB and 97% of the gene-variant mappings based on 180,000 PubMed abstracts.
  
  
  BACKGROUND
  http://bioai4core.fulton.asu.edu/snpshot.
authors.affiliation: Computer Science Department, Arizona State University, 699 S Mill Ave., Tempe, AZ 85281, USA. jorg.hakenberg@roche.com
authors.forename: Jörg
authors.initials: J
authors.lastname: Hakenberg
authors.forename: Dmitry
authors.initials: D
authors.lastname: Voronov
authors.forename: Võ Hà
authors.initials: VH
authors.lastname: Nguyên
authors.forename: Shanshan
authors.initials: S
authors.lastname: Liang
authors.forename: Saadat
authors.initials: S
authors.lastname: Anwar
authors.forename: Barry
authors.initials: B
authors.lastname: Lumpkin
authors.forename: Robert
authors.initials: R
authors.lastname: Leaman
authors.forename: Luis
authors.initials: L
authors.lastname: Tari
authors.forename: Chitta
authors.initials: C
authors.lastname: Baral
mesh_terms: D000818:Animals; D057225:Data Mining / Q000379:methods*; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics*; D056726:Genetic Association Studies / Q000379:methods; D006801:Humans; D051188:Knowledge Bases; D051379:Mice; D010597:Pharmacogenetics / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D039781:PubMed; D051381:Rats