ROC analysis: applications to the classification of biological sequences and 3D structures
ROC analysis: applications to the classification of biological sequences and 3D structures
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DOI：
10.1093/bib/bbm064
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发表时间：
2008-05-01
影响因子：
9.5
通讯作者：
Pongor, Sandor
中科院分区：
文献类型：
--
作者：
Sonego, Paolo;Kocsor, Andras;Pongor, Sandor
ROC（受试者操作者特征）分析是一种用于评估分类算法性能的视觉和数值方法，例如用于从序列数据预测结构和功能的分类算法。本文综述了ROC分析的基本概念，并使用序列和结构比较的例子解释结果。我们概述了可用的程序，并提供基因组/蛋白质组数据的评估准则，特别是在生物信息学中使用的大型和异构数据库的应用。
ROC (receiver operator characteristics) analysis is a visual as well as numerical method used for assessing the performance of classification algorithms, such as those used for predicting structures and functions from sequence data. This review summarizes the fundamental concepts of ROC analysis and the interpretation of results using examples of sequence and structure comparison. We overview the available programs and provide evaluation guidelines for genomic/proteomic data, with particular regard to applications to large and heterogeneous databases used in bioinformatics.