中文摘要：

为提高蛋白质二级结构预测的精确度,提出并构建精确的径向基神经网络、广义回归神经网络,并基于5位编码和Profile编码,采用不同大小的滑动窗口,利用交叉检证法构建多个径向基网络预测器,分别对蛋白质二级结构进行预测,得到了较好的实验结果,其中aveQ3提高到70.96%。结果表明,径向基神经网络模型能有效提高预测精确度,也证明了实验方法的有效性和可行性。

英文摘要：

In order to improve the prediction accuracy of protein secondary structure, exact radial basis function neural network and generalized regression neural network are presented.Multi-radial basis network predictors are established based on 5 encoding, Profile encoding, different sliding windows and cross validation method.These predictors are used to predict protein secondary structure, and it gets preferable results.Thereinto, aveQ3 is improved to 70.96%.The results not only show radial basis network models can increase the prediction accuracy efficiently,but also prove the validity and feasibility of these motheds.