A Hopfield Neural Network Based Algorithm for RNA Secondary Structure Prediction

Qi Liu, X. Ye, Yin Zhang
{"title":"A Hopfield Neural Network Based Algorithm for RNA Secondary Structure Prediction","authors":"Qi Liu, X. Ye, Yin Zhang","doi":"10.1109/IMSCCS.2006.9","DOIUrl":null,"url":null,"abstract":"In this paper a Hopfield neural network (HNN) based parallel algorithm is presented for predicting the secondary structure of ribonucleic acids (RNA). The HNN here is used to find the near-maximum independent set of an adjacent graph made of RNA base pairs and then compute the stable secondary structure of RNA. We modified the motion equation proposed in paper to reflect more biological essence of RNA secondary structure in which the ther mo dynamic parameters of base pair is used in our algorithm to control the variation rate of inhibitory and encouragement terms in the equation. Comparisons with the algorithm presented in paper and other two classical prediction methods (Zuker 's and Nussinov 's) show that our method is more sensitive and specific. In addition, our algorithm can be very efficient and be applied to sequences up to several thousands of base long with more degree of parallelism","PeriodicalId":202629,"journal":{"name":"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMSCCS.2006.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

Abstract

In this paper a Hopfield neural network (HNN) based parallel algorithm is presented for predicting the secondary structure of ribonucleic acids (RNA). The HNN here is used to find the near-maximum independent set of an adjacent graph made of RNA base pairs and then compute the stable secondary structure of RNA. We modified the motion equation proposed in paper to reflect more biological essence of RNA secondary structure in which the ther mo dynamic parameters of base pair is used in our algorithm to control the variation rate of inhibitory and encouragement terms in the equation. Comparisons with the algorithm presented in paper and other two classical prediction methods (Zuker 's and Nussinov 's) show that our method is more sensitive and specific. In addition, our algorithm can be very efficient and be applied to sequences up to several thousands of base long with more degree of parallelism
基于Hopfield神经网络的RNA二级结构预测算法
本文提出了一种基于Hopfield神经网络(HNN)的预测核糖核酸(RNA)二级结构的并行算法。这里的HNN用于寻找由RNA碱基对组成的相邻图的近极大独立集,然后计算RNA的稳定二级结构。我们对文中提出的运动方程进行了修改,使其更能反映RNA二级结构的生物学本质,算法中使用碱基对的其他动力学参数来控制方程中抑制项和激励项的变化率。与本文算法和其他两种经典预测方法(Zuker和Nussinov)的比较表明,本文方法具有更高的灵敏度和特异性。此外,我们的算法可以非常有效地应用于长达数千个碱基的序列,并且具有更高的并行度
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信