基于茎区的神经网络方法预测RNA二级结构

广西师范大学学报（自然科学版） ›› 2011, Vol. 29 ›› Issue (3): 142-146.

基于茎区的神经网络方法预测RNA二级结构

许丹, 王爱荣, 李金铭

福建农林大学计算机与信息学院,福建福州350002

收稿日期:2011-05-16 出版日期:2011-08-20 发布日期:2018-12-03
通讯作者: 李金铭(1961—),男,辽宁清原人,福建农林大学副教授。E-mail:lljjmm888888@163.com
基金资助:
福建省自然科学基金资助项目(2006J0018);国家自然科学基金资助项目(30800713)

Prediction of RNA Secondary Structure by Using the NeuralNetwork of Stems

XU Dan, WANG Ai-rong, LI Jin-ming

College of Computer and Information,Fujian Agriculture and ForestryUniversity,Fuzhou Fujian 350002,China

Received:2011-05-16 Online:2011-08-20 Published:2018-12-03

摘要/Abstract

摘要： RNA二级结构预测是生物信息学的一个重要研究内容。作为预测方法之一的神经网络已被广泛应用于蛋白质结构预测,但在RNA二级结构的应用甚少。本文改进传统预测RNA二级结构的Hopfield神经网络。算法以茎作为网络神经元,通过与相似结构茎区的比对,初始化神经元,并据此修改网络的激励系数。实验把改进后算法与改进前2种算法、Mfold、RNAStructure比较,结果表明本文提出的算法对序列长度较小并且保守性较好的tRNA分子有很好的效果。

关键词: Hopfield神经网络, RNA二级结构, 茎区, tRNA

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 improvedalgorithm is compared to two kinds of unimproved algorithms,Mfold and RNAStructure.Experiments shows that the proposed algorithm has very good results insmaller and better conservative tRNA molecules.

Key words: Hopfield neural network, RNA secondary structure, stem, tRNA

中图分类号:

Q811

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.

XU Dan, WANG Ai-rong, LI Jin-ming. Prediction of RNA Secondary Structure by Using the NeuralNetwork of Stems[J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(3): 142-146.

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