基于GA-BP核酸序列的StSUT2结构预测

Zhengwei Zhu, Yuying Guo
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引用次数: 0

摘要

本文提出的蛋白质二级结构预测系统是马铃薯生物信息研究平台的一个子系统。提出的方法是一种新颖实用的PSS预测方法,该方法基于核酸序列(NAS),采用组合神经网络(CNN),并采用改进的遗传算法(GA)对CNN的连接权进行优化。实验结果表明,该方法不仅可行,而且与传统的PSS预测方法相比,预测精度更高,使用更方便,搜索速度更快,具有一定的保密性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
StSUT2 Structure Prediction Based on Nucleic Acid Sequence Using GA-BP
The protein secondary structure (PSS) prediction system presented in this paper is a subsystem of potato bioinformation research platform. The proposed method is a novel and practical PSS prediction method, which is based on nucleic acid sequence (NAS), uses an combined neural network (CNN) and takes an improved genetic algorithm (GA) to optimize the connection weights of CNN. The experimental results indicate that, not only the proposed method is feasible, but compared with the traditional PSS prediction methods, its prediction accuracy is higher, its use is more convenient, its search speed is faster and it has confidentiality in a certain degree.
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