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Importance of RNA secondary structure information for yeast donor and acceptor splice site predictions by neural networks

Paper ID Volume ID Publish Year Pages File Format Full-Text
15414 1411 2006 8 PDF Available
Title
Importance of RNA secondary structure information for yeast donor and acceptor splice site predictions by neural networks
Abstract

Previously, Patterson et al. showed that mRNA structure information aids splice site prediction in human genes [Patterson, D.J., Yasuhara, K., Ruzzo, W.L., 2002. Pre-mRNA secondary structure prediction aids splice site prediction. Pac. Symp. Biocomput. 7, 223–234]. Here, we have attempted to predict splice sites in selected genes of Saccharomyces cerevisiae using the information obtained from the secondary structures of corresponding mRNAs. From Ares database, 154 genes were selected and their structures were predicted by Mfold. We selected a 20-nucleotide window around each site, each containing 4 nucleotides in the exon region. Based on whether the nucleotide is in a stem or not, the conventional four-letter nucleotide alphabet was translated into an eight-letter alphabet. Two different three-layer-based perceptron neural networks were devised to predict the 5′ and 3′ splice sites. In case of 5′ site determination, a network with 3 neurons at the hidden layer was chosen, while in case of 3′ site 20 neurons acted more efficiently. Both neural nets were trained applying Levenberg–Marquardt backpropagation method, using half of the available genes as training inputs and the other half for testing and cross-validations. Sequences with GUs and AGs non-sites were used as negative controls. The correlation coefficients in the predictions of 5′ and 3′ splice sites using eight-letter alphabet were 98.0% and 69.6%, respectively, while these values were 89.3% and 57.1% when four-letter alphabet is applied. Our results suggest that considering the secondary structure of mRNA molecules positively affects both donor and acceptor site predictions by increasing the capacity of neural networks in learning the patterns.

Keywords
Splice site prediction; Gene prediction; Neural network; RNA structure; Saccharomyces cerevisiae
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Importance of RNA secondary structure information for yeast donor and acceptor splice site predictions by neural networks
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 30, Issue 1, February 2006, Pages 50–57
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us