title: Mining housekeeping genes with a Naive Bayes classifier.
abstract: BACKGROUND
  Traditionally, housekeeping and tissue specific genes have been classified using direct assay of mRNA presence across different tissues, but these experiments are costly and the results not easy to compare and reproduce.
  
  
  RESULTS
  In this work, a Naive Bayes classifier based only on physical and functional characteristics of genes already available in databases, like exon length and measures of chromatin compactness, has achieved a 97% success rate in classification of human housekeeping genes (93% for mouse and 90% for fruit fly).
  
  
  CONCLUSIONS
  The newly obtained lists of housekeeping and tissue specific genes adhere to the expected functions and tissue expression patterns for the two classes. Overall, the classifier shows promise, and in the future additional attributes might be included to improve its discriminating power.
authors.affiliation: School of Informatics, the University of Edinburgh, Edinburgh EH8 9LE, UK. ldeferra@inf.ed.ac.uk
authors.forename: Luna
authors.initials: L
authors.lastname: De Ferrari
authors.forename: Stuart
authors.initials: S
authors.lastname: Aitken
mesh_terms: D000818:Animals; D001483:Base Sequence; D001499:Bayes Theorem; D002843:Chromatin / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D018076:DNA, Complementary / Q000235:genetics; D030541:Databases, Genetic; D004330:Drosophila / Q000235:genetics*; D005091:Exons / Q000235:genetics; D006801:Humans; D051379:Mice; D009928:Organ Specificity / Q000235:genetics; D012333:RNA, Messenger / Q000235:genetics; D012372:ROC Curve
chemical_list: D002843:Chromatin; D018076:DNA, Complementary; D012333:RNA, Messenger