Abstract
Prediction of exonic and intronic regions is an important problem of bioinformatics, which has been solved with a set of medium accuracy coding measures. In this work, we propose a new methodology for the prediction of exons and introns based on a cryptanalysis method of Kasiski, using variants of three classical coding measures: codon usage, amino acid usage, and codon preference. We validated our approach testing a set of 178 sequence of different length, improving the prediction of exons level reported by Fickett. Additionally we introduce the first results of introns prediction with an accuracy level of 83.4%.
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Aguilar R., M., Fraire H., H., Cruz R., L., González B., J.J., Castilla V., G., Gómez S., C.G. (2007). Classic Cryptanalysis Applied to Exons and Introns Prediction. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74484-9_50
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DOI: https://doi.org/10.1007/978-3-540-74484-9_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74482-5
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