Predicting Melting Temperature (Tm) of DNA Duplex Based on Neural Network

  • Xiangrong Liu
  • Wenbin Liu
  • Juan Liu
  • Linqiang Pan
  • Jin Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4115)


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.


Neural Network Random Real Number Biomolecular Computer Nucleic Acid Oligomer Similar Thermodynamic Stability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiangrong Liu
    • 1
  • Wenbin Liu
    • 2
  • Juan Liu
    • 3
  • Linqiang Pan
    • 1
  • Jin Xu
    • 1
  1. 1.Research Institute of biomolecular ComputerHuazhong University of Science and TechnologyWuhan CityChina
  2. 2.School of Computer Science and EngineeringWenzhou Normal CollegeWenzhou CityChina
  3. 3.The Department of Electronic Science and TechnologyHuazhong University of Science and TechnologyWuhan CityChina

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