Bioinformatics Vol. 17 no. 90001 2001
Pages S90-S96
© 2001 Oxford University Press
Promoter prediction in the human genome
Informatics Research, Celera Genomics, 45 West Gude Drive, Rockville, MD-20850, USA
Received on February 5, 2001
; revised on March 29, 2001
; accepted on March 29, 2001
Computational prediction of eukaryotic polII promoters has been one of the most elusive problems despite considerable effort devoted to the study. Researchers have looked for various types of signals around the transcriptional start site (TSS), viz. oligo-nucleotide statistics, potential binding sites for core factors, clusters of binding sites, proximity to CpG islands etc.. The proximity of CpG islands to gene starts is now a well established fact, although until recently, it was based on very little genomic data. In this work we explore the possibility of enhancing the promoter prediction accuracy by combining CpG island information with a few other, biologically motivated, seemingly independent signals, that cover most of the known knowledge. We benchmarked the method on a much larger genomic datasets compared to previous studies. We were able to improve slightly upon current prediction accuracy. Furthermore, we observe that CpG islands are the most dominant signals and the other signals do not improve the prediction. This suggests that the computational prediction of promoters for genes with no associated CpG-island (typically having tissue-specific expression) looking only at the immediate neighborhood of the TSS may not even be possible. We suggest some biological experiments and studies to better understand the biology of transcription.
Contact: Sridhar.Hannenhalli{at}celera.com; Samuel.Levy{at}celera.com
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