Abstract
In DNA computing, similar thermodynamic stability of the encoding DNA sequences is conduced to improve the reliability and precision of the computing process. The melting temperature is a suitable parameter used to evaluating the stability of DNA duplex. Traditional method to predict Tm in biological engineering may exist lager error for a few sequences. Thus it misfits the lager amount of DNA sequences in DNA computing. In this paper, we introduced artificial neural network to predict the Tm based on Next-Nearest-Neighbor model. Our result shows that the methods have a higher precision than TP methods based on nearest-neighbor model.
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Liu, X., Liu, W., Liu, J., Pan, L., Xu, J. (2006). Predicting Melting Temperature (Tm) of DNA Duplex Based on Neural Network. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence and Bioinformatics. ICIC 2006. Lecture Notes in Computer Science(), vol 4115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816102_30
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DOI: https://doi.org/10.1007/11816102_30
Publisher Name: Springer, Berlin, Heidelberg
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