预测蛋白质亚细胞定位的杂交系统

Shu-Bo Zhang, J. Lai
{"title":"预测蛋白质亚细胞定位的杂交系统","authors":"Shu-Bo Zhang, J. Lai","doi":"10.1109/BMEI.2009.5305500","DOIUrl":null,"url":null,"abstract":"Protein subcellular localization prediction is important to functional annotation of protein. In this study, a hybrid system based on the sorting mechanism of protein was proposed to predict protein subcellular localization. At first, an unknown protein sequence was divided into two sub-sequences at certain position, then features were extracted from them and combined into a fusion feature vector to describe the whole protein sequence. Secondly, an optimal sub-classifier was searched out to discriminate each kind of protein from the others through iterative searching strategy. Finally, all of the sub-classifiers were combined into a hybrid system to predict subcellular localization of unknown protein. Experimental results on two public datasets showed that our hybrid system is an effective way for the prediction of protein subcellular localization, and it has higher accuracy than others.","PeriodicalId":6389,"journal":{"name":"2009 2nd International Conference on Biomedical Engineering and Informatics","volume":"69 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Hybrid System for Prediction of Protein Subcellular Localization\",\"authors\":\"Shu-Bo Zhang, J. Lai\",\"doi\":\"10.1109/BMEI.2009.5305500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Protein subcellular localization prediction is important to functional annotation of protein. In this study, a hybrid system based on the sorting mechanism of protein was proposed to predict protein subcellular localization. At first, an unknown protein sequence was divided into two sub-sequences at certain position, then features were extracted from them and combined into a fusion feature vector to describe the whole protein sequence. Secondly, an optimal sub-classifier was searched out to discriminate each kind of protein from the others through iterative searching strategy. Finally, all of the sub-classifiers were combined into a hybrid system to predict subcellular localization of unknown protein. Experimental results on two public datasets showed that our hybrid system is an effective way for the prediction of protein subcellular localization, and it has higher accuracy than others.\",\"PeriodicalId\":6389,\"journal\":{\"name\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"volume\":\"69 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2009.5305500\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2009.5305500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

蛋白质亚细胞定位预测是蛋白质功能解释的重要内容。本研究提出了一种基于蛋白质分选机制的杂交系统来预测蛋白质亚细胞定位。首先,将未知蛋白质序列在特定位置划分为两个子序列,然后从中提取特征并组合成一个融合特征向量来描述整个蛋白质序列。其次,通过迭代搜索策略,找出最优子分类器,将每种蛋白质与其他蛋白质区分开来;最后,将所有的亚分类器组合成一个杂交系统来预测未知蛋白的亚细胞定位。在两个公开数据集上的实验结果表明,该混合系统是一种有效的蛋白质亚细胞定位预测方法,具有较高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Hybrid System for Prediction of Protein Subcellular Localization
Protein subcellular localization prediction is important to functional annotation of protein. In this study, a hybrid system based on the sorting mechanism of protein was proposed to predict protein subcellular localization. At first, an unknown protein sequence was divided into two sub-sequences at certain position, then features were extracted from them and combined into a fusion feature vector to describe the whole protein sequence. Secondly, an optimal sub-classifier was searched out to discriminate each kind of protein from the others through iterative searching strategy. Finally, all of the sub-classifiers were combined into a hybrid system to predict subcellular localization of unknown protein. Experimental results on two public datasets showed that our hybrid system is an effective way for the prediction of protein subcellular localization, and it has higher accuracy than others.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Novel Approach for Blood Vessel Edge Detection in Retinal Images Skin Response During Irradiation by Intense Pulsed Light Based on Optical Imaging Technology and Histology Physical Properties of LYSO Scintillator for NN-PET Detectors A High Security Framework for SMS An Efficient Antenna Selection Algorithm for MIMO Systems
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1