数据采集与处理2019，Vol.34Issue(2)：303-311,9.DOI:10.16337/j.1004-9037.2019.02.013
一种基于压缩感知和动态时间规整的信号肽特征提取新算法
A New Algorithm of Feature Extraction for Signal Peptide Based on Compressed Sensing and Dynamic Time Warping
摘要
Abstract
Identifying signal peptide accurately is significant for protein research and localization. This paper presents a new method to extract high discriminant features for signal peptide sequence. Firstly, features based on compressed sensing are extracted by projecting a high-dimensional sequence onto a lowdimensional space, which remove redundant data while preserving the important information. And then dynamic time warping (DTW) algorithm is introduced to create the new features. The features extracted by the new method can reflect the important information of amino acid composition, sequence order and structure in the signal peptide, and also can nonlinearly align the different regions of signal peptide in the time dimension. Therefore the effective feature expression of the signal peptide for machine learning algorithm is provided. Experimental results show that the recognition accuracies with the extracted features are 99.65％, 98.05％ and 98.56％ respectively in the three datasets Eukaryotes, Gram + bacteria and Gram-bacteria. Moreover, the new method can be simply applied to the identification of several biological sequences.关键词
信号肽/动态时间规整/压缩感知/特征提取/机器学习Key words
signal peptide/dynamic time warping/compressed sensing/feature extraction/machine learning分类
信息技术与安全科学引用本文复制引用
张洋俐君,高翠芳,陈卫,田丰伟..一种基于压缩感知和动态时间规整的信号肽特征提取新算法[J].数据采集与处理,2019,34(2):303-311,9.基金项目
国家自然科学基金青年基金(61402202)资助项目 （61402202）
中国博士后科学基金(2015M581724)资助项目 （2015M581724）
江苏省博士后科学基金(1401099C)资助项目 （1401099C）
江苏省自然科学基金青年基金(BK20150124)资助项目 （BK20150124）
