[1]汪方良,施慧彬. 基于OpenCL的RNA二级结构预测算法[J].计算机技术与发展,2017,27(09):1-6.
　WANG Fang-liang,SHI Hui-bin. Secondary Structure Prediction of RNA Based on OpenCL[J].,2017,27(09):1-6.
点击复制

 基于OpenCL的RNA二级结构预测算法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年09期
页码:
1-6
栏目:
智能、算法、系统工程
出版日期:
2017-09-10

文章信息/Info

Title:
 Secondary Structure Prediction of RNA Based on OpenCL
文章编号:
1673-629X（2017)09-0001-06
作者:
 汪方良; 施慧彬
 南京航空航天大学 计算机科学与技术学院
Author(s):
 WANG Fang-liang; SHI Hui-bin
关键词:
 ; RNA二级结构预测; 假结; OpenCL; 异构计算
Keywords:
 ; RNA secondary structure; pseudoknots; OpenCL; heterogeneous computing
分类号:
TP311
文献标志码:
A
摘要:
 
包含假结的RNA二级结构预测在计算分子生物学中一直是一个重要的研究领域,而预测包含任意类型假结结构已被证明为NP完全问题.为了解决此类问题,在CPU平台上实现了一种改进的遗传算法.该算法可预测包含两类假结结构的RNA序列,敏感性可达到0.775,阳性预测率可达到0.8225.针对基于遗传算法带假结的RNA二级结构预测低效的问题,提出了基于OpenCL的异构并行加速算法.该算法在分析串行算法并行性的基础上,在种群迭代进化阶段进行异构加速,并基于GPU设备和OpenCL编程框架改进算法过程.为验证所提算法的可行性和有效性,基于相同的测试集进行了实验测试.测试结果表明,相对于串行算法,改进后的异构并行加速算法平均可实现2.72倍的速度提升,有效降低了RNA二级结构预测的耗时,提高了算法模拟预测效率.
Abstract:
 redicting RNA secondary structure is an important field in computational molecular biology especially including pseudoknots. However,predicting RNA secondary structure with all kinds of pseudoknots has been proven to be an NP-complete problem. To solve it, an improved genetic algorithm is proposed in CPU platform,which can predict two kinds of pseudoknots. Its sensitivity can reach 0. 775 and its positive predictive value can reach 0. 8225. The prediction of RNA secondary structure with pseudoknots based on genetic algo-rithm is inefficient. To solve it,an accelerated algorithm based on OpenCL is presented,which accelerates the period of individual evolu-tion according to the analysis of parallelizability of serial prediction algorithm. Then the algorithm established with GPU based on OpenCL is promoted. The contrast experiments with the same test set have been conducted compared with other algorithms. The experimental re-sults show that the improved heterogeneous parallel algorithm has acquired 2. 72 times faster average operation rate than others,reducing the computing time effectively and improving the efficiency of prediction.

相似文献/References:

[1]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
　ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(09):1.
[2]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
　LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(09):5.
[3]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
　HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(09):13.
[4]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
　HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(09):21.
[5]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
　LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(09):25.
[6]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
　WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(09):29.
[7]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
　LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(09):34.
[8]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
　SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(09):38.
[9]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
　YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(09):43.
[10]余松平[][],蔡志平[],吴建进[],等. GSM-R信令监测选择录音系统设计与实现[J].计算机技术与发展,2014,24(07):47.
　YU Song-ping[][],CAI Zhi-ping[] WU Jian-jin[],GU Feng-zhi[]. Design and Implementation of an Optional Voice Recording System Based on GSM-R Signaling Monitoring[J].,2014,24(09):47.

更新日期/Last Update: 2017-10-19