真核蛋白质的亚细胞位点预测研究进展  

Progress in Predicting Subcellular Localizations of Eukaryotic Proteins

作　　者：崔琳[1] 张朝军[1] 肖卫东[1] 李祥生[1] 李立奇[1] 杨桦[1] 

机构地区：[1]第三军医大学新桥医院普通外科,重庆400037

出　　处：《现代生物医学进展》2015年第28期5582-5585,共4页Progress in Modern Biomedicine

基　　金：国家自然科学基金项目(81302134)

摘　　要：研究真核蛋白质的亚细胞位点是了解真核蛋白质功能,深入研究蛋白质相关信号通路内在机制的基础。同时,可以为了解疾病发病机制及为新药研发提供帮助。因此,研究真核蛋白质的亚细胞位点意义十分重大。随着基因组测序的完成,真核蛋白质序列信息增长迅速,为真核蛋白质亚细胞位点的研究提出了更多的挑战。传统的实验法难以满足蛋白质信息量迅速增长的需求。而采用生物信息学手段处理大规模数据的计算预测方法,可在较短时间内获得大量真核蛋白质亚细胞位点信息,弥补了实验法的不足。因此,运用计算预测法预测真核蛋白质的亚细胞位点成为生物信息学领域的研究热点之一。本文主要从提取真核蛋白质的特征信息、计算预测方法及预测效果的评价三个方面,介绍近年来真核蛋白质亚细胞位点预测的研究进展。Identification of eukaryotic protein subcellular localization is very important for understanding eukaryotic protein functions and internal mechanisms of related signal pathways. Meanwhile, it contributes to revealing the pathogenesis of diseases and the development of new drugs. Consequently, it is of great significance to study eukaryotic protein subcellular localization. With the completion of genome sequencing, the information of eukaryotic protein sequences increases rapidly, which brings more challenges to identify eukaryotic protein subcellular localization. Since experimental determinations of eukaryotic protein subcellular localization are tedious, costly and time-consuming, especially for rapidly growing information of proteins, it is highly desirable to develop computational approaches to predict eukaryotic protein subcellular localizations. This paper mainly introduces the progress in predicting eukaryotic protein subcellular localization among the past years. It consists of three aspects： protein feature representation, algorithm selection for classification and assessment of prediction.

关 键 词：真核蛋白质 亚细胞位点 预测 算法 

分 类 号：Q51[生物学—生物化学] Q71