title: CoPub Mapper: mining MEDLINE based on search term co-publication.
abstract: BACKGROUND
  High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to identify biological similarities between genes, publications from MEDLINE were identified in which pairs of gene names and combinations of gene name with specific keywords were co-mentioned.
  
  
  RESULTS
  MEDLINE search strings for 15,621 known genes and 3,731 keywords were generated and validated. PubMed IDs were retrieved from MEDLINE and relative probability of co-occurrences of all gene-gene and gene-keyword pairs determined. To assess gene clustering according to literature co-publication, 150 genes consisting of 8 sets with known connections (same pathway, same protein complex, or same cellular localization, etc.) were run through the program. Receiver operator characteristics (ROC) analyses showed that most gene sets were clustered much better than expected by random chance. To test grouping of genes from real microarray data, 221 differentially expressed genes from a microarray experiment were analyzed with CoPub Mapper, which resulted in several relevant clusters of genes with biological process and disease keywords. In addition, all genes versus keywords were hierarchical clustered to reveal a complete grouping of published genes based on co-occurrence.
  
  
  CONCLUSIONS
  The CoPub Mapper program allows for quick and versatile querying of co-published genes and keywords and can be successfully used to cluster predefined groups of genes and microarray data.
authors.affiliation: Department of Molecular Design & Informatics, Organon NV, P.O. Box 20, 5340 BH Oss, The Netherlands. blaise.alako@wur.nl
authors.forename: Blaise T F
authors.initials: BT
authors.lastname: Alako
authors.forename: Antoine
authors.initials: A
authors.lastname: Veldhoven
authors.forename: Sjozef
authors.initials: S
authors.lastname: van Baal
authors.forename: Rob
authors.initials: R
authors.lastname: Jelier
authors.forename: Stefan
authors.initials: S
authors.lastname: Verhoeven
authors.forename: Ton
authors.initials: T
authors.lastname: Rullmann
authors.forename: Jan
authors.initials: J
authors.lastname: Polman
authors.forename: Guido
authors.initials: G
authors.lastname: Jenster
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D016206:Databases, Bibliographic; D016208:Databases, Factual; D030541:Databases, Genetic; D020224:Expressed Sequence Tags; D005189:False Positive Reactions; D020869:Gene Expression Profiling; D005796:Genes; D006801:Humans; D016247:Information Storage and Retrieval; D016239:MEDLINE; D015201:Meta-Analysis as Topic; D008958:Models, Molecular; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D039781:PubMed; D012372:ROC Curve; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software; D013358:Subject Headings; D014584:User-Computer Interface; D018875:Vocabulary, Controlled