计算机工程与应用2012，Vol.48Issue(6)：126-128,3.DOI:10.3778/j.issn.1002-8331.2012.06.037
一种新的蛋白质亚细胞定位预测方法
Novel approach to prediction of protein subcellular localization
摘要
Abstract
It is one of basic problems of proteomics to identify the subcellular locations of a protein. It makes the problem more complicated that some proteins may simultaneously exist in two or more than two subcellular locations. Gene Ontology and pseudo amino acid composition are respectively employed to represent a protein as a real values vector. The idea of Ranking initiating from multi-label learning community is adopted to compute a score vector V, each component value of which indicates the probability that a protein of the corresponding subcellular location.The nearest neighbor algorithm is then employed to predict the number n of subcellular localization of human proteins. Finally, the n subcellular locations corresponding to the top n scores components in V are assign to the query protein.关键词
蛋白质亚细胞定位/多标记学习/Gene Ontology/最近邻算法Key words
protein subcellular localization/multi-label learning/Gene Ontology/k-nearest neighbors algorithm分类
信息技术与安全科学引用本文复制引用
程昔恩,吴志诚..一种新的蛋白质亚细胞定位预测方法[J].计算机工程与应用,2012,48(6):126-128,3.基金项目
国家自然科学基金(No.60961003) （No.60961003）
江西省自然科学基金(No.2010GQS0127). （No.2010GQS0127）
