Modeling splicing sites with pairwise correlations.

Masanori Arita; Koji Tsuda; Kiyoshi Asai

doi:10.1093/bioinformatics/18.suppl_2.s27

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Modeling splicing sites with pairwise correlations.

Masanori Arita·Koji Tsuda·Kiyoshi Asai

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Abstract

MOTIVATION: A new method for finding subtle patterns in sequences is introduced. It approximates the multiple correlations among residuals with pair-wise correlations, with the learning cost O(m(2)n) where n is the number of training sequences, each of length m. The method suits to model splicing sites in human DNA, which are reported to have higher-order dependencies. RESULTS: By computational experiments, the prediction accuracy of our model was shown to surpass that of previously reported Markov models for the prediction of acceptor sites in human. AVAILABILITY: The C++ source code is available on request from the authors.

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Algorithms Base Pairing Chromosome Mapping Computer Simulation Genome, Human Humans Models, Genetic Models, Statistical RNA Splice Sites Sequence Alignment Sequence Analysis, DNA Sequence Homology, Nucleic Acid Software Statistics as Topic Comparative Study Evaluation Study Journal Article

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Masanori Arita, Koji Tsuda, Kiyoshi Asai. 2002. Modeling splicing sites with pairwise correlations.. https://doi.org/10.1093/bioinformatics%2F18.suppl_2.s27

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