A New Subcellular Localization Predictor for Human Proteins Considering the Correlation of Annotation Features and Protein Multi-localization

摘要：

　　unction of the protein.While experimental method to identify the subcellular localization of proteins will cost a lot of time,it is necessary to utilize computational approaches for dealing with large scale proteins of unknown location.Current predictors mostly consider the annotation-based features but few of them take their correlation into account.Moreover,most of predictors can only deal with single-locational proteins,while a lot of proteins bear multi-locational characteristics,which play important roles in many biological processes.In this paper,we propose a novel prediction method,which extracts features from prior biological knowledge by considering the correlation between annotation terms.The new method can also deal with the multi-localization problem.We compared the performance of the proposed method with other predictors on four datasets.The result shows that our method is outperform than others.

关键词： Subcellular localization Multi-label Correlation Gene Ontology

作者: Hang Zhou Yang Yang Hong-Bin Shen

作者单位: Key Laboratory of System Control and Information Processing,Institute of Image Processing and Patter Department of Computer Science,Shanghai Jiao Tong University,Shanghai 200240,China

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 499-512

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）