Abstract:

The prediction of protein secondary structure is one of the major issues in Bioinformatics. As one of the researches of KDTICM theory, a multiclassification algorithm based on structure sequence is proposed, which is based on knowledge discovery in database* (KDD*) model. The SAC algorithm can effectively solve the problem of protein secondary structure prediction. The algorithm’s accuracy exceeded by 85% by using the reduction of knowledge base through the setting of the confidence threshold value. A compound pyramid model is built with the SAC algorithm being regarded as a kernel. Experimental results show that the predictive accuracy exceeded by 80% when using in the datasets of RS126,CB513 and ILP, which is equivalent or even excels known national and international levels.