Hybrid model of ANN/HMM for protein secondary structure prediction
应用ANN/HMM混合模型预测蛋白质二级结构*

Aimed at the lower accuracy of 3-state hidden Markov model for protein secondary structure prediction,proposed 15-state HMM.Using modified algorithm of HMM to predict secondary structure combined with BP neural networks.Selected 492 proteins from the dataset CB513,and divided them into 7 even subsets.Applied the hybrid model to predict secondary structure and evaluated its accuracy by 7-fold cross validation.The hybrid model appeared to be very efficient,with Q3 score of 77.21% and SOV of 72.52%.The results show that the hybrid model not only captures the local information,but also considers the long-distance information.So it gets higher prediction accuracy.