Predicting Melting Temperature (Tm) of DNA Duplex Based on Neural Network
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.
KeywordsNeural Network Random Real Number Biomolecular Computer Nucleic Acid Oligomer Similar Thermodynamic Stability
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