title: A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.
abstract: BACKGROUND
  The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level.
  
  
  RESULTS
  The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists.
  
  
  CONCLUSIONS
  The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining system that effectively predicts implicit gene-gene interaction relationships and networks in a genome-wide scope.
authors.forename: Zuoshuang
authors.initials: Z
authors.lastname: Xiang
authors.forename: Tingting
authors.initials: T
authors.lastname: Qin
authors.forename: Zhaohui S
authors.initials: ZS
authors.lastname: Qin
authors.forename: Yongqun
authors.initials: Y
authors.lastname: He
mesh_terms: D000465:Algorithms; D002002:Brucella / Q000235:genetics; D016000:Cluster Analysis; D057225:Data Mining / Q000379:methods*; D004926:Escherichia coli / Q000235:genetics; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods*; D046650:Medical Subject Headings