Mining housekeeping genes with a Naive Bayes classifier
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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.
De Ferrari , L & Aitken , S 2006 , ' Mining housekeeping genes with a Naive Bayes classifier ' , BMC Genomics , vol. 7 , 277 . https://doi.org/10.1186/1471-2164-7-277
© 2006 De Ferrari and Aitken; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DescriptionThe first author was supported by the Student Awards Agency for Scotland. The second author is supported by BBSRC grant BBS RC BB/D006473/1, and under the Advanced Knowledge Technologies (AKT) Interdisciplinary Research Collaboration (IRC), which is sponsored by the UK Engineering and Physical Sciences Research Council under grant number GR/N15764/01.
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