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Bioinformatics Advance Access published online on March 15, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti387
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received December 16, 2004
Revised February 24, 2005
Accepted March 9, 2005

Article

Promoter modeling: the case study of mammalian histone promoters

Rajesh Chowdhary 1, R. Ayesha Ali 2, Werner Albig 3, Detlef Doenecke 3, and Vladimir B. Bajic 1*

1 Knowledge Extraction Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613
2 Department of Statistics and Applied Probability, National University of Singapore, 3 Science Drive 2, Singapore 117543
3 Department of Molecular Biology, Biochemistry and Molecular Cell Biology, University of Göttingen, Humboldtallee 23, 37073 Göttingen, Germany

* To whom correspondence should be addressed.
Vladimir B. Bajic, E-mail: bajicv{at}i2r.a-star.edu.sg


  Abstract

Motivation: Histone proteins play important roles in chromosomal functions. They are significantly evolutionarily conserved across species, which suggests similarity in their transcription regulation. The abundance of experimental data on histone promoters provide an excellent background for evaluation of computational methods. Our study addresses the issue of how well computational analysis can contribute to unveil the biologically relevant content of promoter regions for a large number of mammalian histone genes taken across several species, and suggests the consensus promoter models of different histone groups.

Results: This is the first study to unveil the detailed promoter structures of all five mammalian histone groups and their subgroups. This is also the most comprehensive computational analysis of histone promoters performed to date. The most exciting fact is that the results correlate very well with the biologically known facts and experimental data. Our analysis convincingly demonstrates that computational approach can significantly contribute to elucidation of promoter content (identification of biologically relevant signals) complementing tedious wet-lab experiments. We believe that this type of analysis can be easily applied to other functional gene classes, thus providing a general framework for modelling promoter groups. These results also provide the basis to hunt for genes co-regulated with histone genes across mammalian genomes.

Supplementary Information: This work is complemented by the supplementary material.


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