  In DNA computing, it is impossible to decide whether a specific hybridization
among complex DNA molecules is effective or not within acceptable time. In
order to address this common problem, we introduce a new method based on the
machine learning technique. First, a sample set is employed to train the
Boosted Tree (BT) algorithm, and the corresponding model is obtained. Second,
this model is used to predict classification results of molecular
hybridizations. The experiments show that the average accuracy of the new
method is over 94.2%, and its average efficiency is over 90839 times higher
than that of the existing method. These results indicate that the new method
can quickly and accurately determine the biological effectiveness of molecular
hybridization for a given DNA design.
