Bioinformatics: the machine learning approach
Bioinformatics: the machine learning approach
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
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A system for utilizing an artificial neural network to predict splice sites in genes has been studied. The neural network uses a sliding window of nucleotides over a gene and predicts possible splice sites. Based on the neural network output, the exact location of the splice site is found using a curve fitting of a parabolic function. The splice site location is predicted without prior knowledge of any sensor signals, like `GT' or `GC' for the donor splice sites, or `AG' for the acceptor splice sites. The neural network has been trained using backpropagation on a set of 16965 genes of the model plant Arabidopsis thaliana. The performance is then measured using a completely distinct gene set of 5000 genes, and verified at a set of 20 genes. The best measured performance on the verification data set of 20 genes, gives a sensitivity of 0.891, a specificity of 0.816 and a correlation coefficient of 0.552.