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On splice site prediction using weight array models: a comparison of smoothing techniques

Leila Taher1,2, Peter Meinicke3 and Burkhard Morgenstern3

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In most eukaryotic genes, protein-coding exons are separated by non-coding introns which are removed from the primary transcript by a process called "splicing". The positions where introns are cut and exons are spliced together are called "splice sites". Thus, computational prediction of splice sites is crucial for gene finding in eukaryotes. Weight array models are a powerful probabilistic approach to splice site detection. Parameters for these models are usually derived from m-tuple frequencies in trusted training data and subsequently smoothed to avoid zero probabilities. In this study we compare three different ways of parameter estimation for m-tuple frequencies, namely (a) non-smoothed probability estimation, (b) standard pseudo counts and (c) a Gaussian smoothing procedure that we recently developed.


PACS

87.14.E- Proteins

87.14.G- Nucleic acids

87.15.B- Structure of biomolecules

02.50.Ng Distribution theory and Monte Carlo studies

02.50.Cw Probability theory

Subjects

Computational physics

Biological physics

Dates

Issue 1 (2007)



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