Abstract
Translation initiation site (TIS) recognition is one of the first steps in gene structure prediction, and one of the common components in any gene recognition system. Many methods have been described in the literature to identify TIS in transcribed sequences such as mRNA, EST and cDNA sequences. However, the recognition of TIS in DNA sequences is a far more challenging task, and the methods described so far for transcripts achieve poor results in DNA sequences. In this work we present the application of response surfaces to the problem of TIS recognition.
Response surfaces are a powerful tool for both classification and regression as they are able to model many different phenomena and construct complex boundaries between classes. Furthermore, the interpretability of the results is very interesting from the point of view of the expert. In this paper we show the use of real-coded genetic algorithms for evolving a response surface that learns to classify TIS. The results obtained in three different organisms are comparable with a well-known classification algorithm with a more interpretable polynomial function.
This work has been financed in part by the Excellence in Research Project P07-TIC-2682 of the Junta de Andalucía.
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del Castillo-Gomariz, R., García-Pedrajas, N. (2011). Translation Initiation Site Recognition by Means of Evolutionary Response Surfaces. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21827-9_39
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DOI: https://doi.org/10.1007/978-3-642-21827-9_39
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