Research article

Mining housekeeping genes with a Naive Bayes classifier

Luna De Ferrari^* and Stuart Aitken

• * Corresponding author: Luna De Ferrari ldeferra@inf.ed.ac.uk

Author Affiliations

School of Informatics, the University of Edinburgh, Edinburgh EH8 9LE, UK

For all author emails, please log on.

BMC Genomics 2006, 7:277 doi:10.1186/1471-2164-7-277

Published: 30 October 2006

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).

Conclusion

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.