A neural network for predicting the stability of DNA/DNA duplexes.
A back-propagation neural network method has been developed to predict the stability of DNA/DNA duplexes. Calculated Tm with the present parameters fits the experimental values within reasonable errors (AD = 1.86 K, SEP = 1.99151, R2 = 0.9894 for NN1; AD = 1.59667 K, SEP = 2.03824, R2 = 0.99371 for NN2) and it has the advantage that the determinations of thermodynamic parameters are not needed.
Liu
Xiaohong
X
Key Laboratory of Bioorganic Phosphorus Chemistry, Ministry of Education, Department of Chemistry, School of Life Sciences and Engineering, Tsinghua University, Beijing, P. R. China.
Ma
Lixin
L
Cheng
Changmei
C
Wang
Yong
Y
Miyajima
Hiromi
H
Zhao
Yufen
Y
D001185:Artificial Intelligence; D020029:Base Pairing; D001483:Base Sequence; D004247:DNA / Q000737:chemistry*; D005544:Forecasting; D008958:Models, Molecular; D008969:Molecular Sequence Data; D016571:Neural Networks, Computer; D009838:Oligodeoxyribonucleotides / Q000737:chemistry*; D013696:Temperature; D013816:Thermodynamics
D009838:Oligodeoxyribonucleotides; D004247:DNA