广西师范大学学报（自然科学版）2011，Vol.29Issue(3)：142-146,5.
基于茎区的神经网络方法预测RNA二级结构
Prediction of RNA Secondary Structure by Using the Neural Network of Stems
摘要
Abstract
RNA secondary structure prediction is an important research field in bioinformatics. As one of the forecasting method,neural network has been widely used in protein structure prediction but very little in RNA secondary structure. The traditional prediction of RNA secondary structure using Hopfield neural network is improved in this paper. Stem is used as the neuron of network in the algorithm. The network incentive factor and the initial value of neurons are modified by alignment with the stem area of similar structure. The improved algorithm is compared to two kinds of unimproved algorithms, Mfold and RNAStructure. Experiments shows that the proposed algorithm has very good results in smaller and better conservative tRNA molecules.关键词
Hopfield神经网络/RNA二级结构/茎区/tRNAKey words
Hopfield neural network/RNA secondary structure/stem/tRNA分类
生物科学引用本文复制引用
许丹,王爱荣,李金铭..基于茎区的神经网络方法预测RNA二级结构[J].广西师范大学学报（自然科学版）,2011,29(3):142-146,5.基金项目
福建省自然科学基金资助项目(2006J0018) （2006J0018）
国家自然科学基金资助项目(30800713) （30800713）
