ROC analysis: applications to the classification of biological sequences and 3D structures

by: Paolo Sonego, Andras Kocsor, Sandor Pongor

Brief Bioinform (11 January 2008), bbm064.

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Abstract

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. 10.1093/bib/bbm064

@article{citeulike:2228320, abstract = {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. 10.1093/bib/bbm064}, author = {Sonego, Paolo and Kocsor, Andras and Pongor, Sandor }, citeulike-article-id = {2228320}, doi = {10.1093/bib/bbm064}, journal = {Brief Bioinform}, keywords = {classification, roc, sequence, statistics, structure}, month = {January}, pages = {bbm064+}, posted-at = {2008-04-23 13:46:17}, priority = {2}, title = {ROC analysis: applications to the classification of biological sequences and 3D structures}, url = {http://dx.doi.org/10.1093/bib/bbm064}, year = {2008} }

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TY - JOUR ID - citeulike:2228320 L3 - citeulike-article-id:2228320 TI - ROC analysis: applications to the classification of biological sequences and 3D structures JF - Brief Bioinform SP - bbm064 N2 - 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. 10.1093/bib/bbm064 KW - classification KW - roc KW - sequence KW - statistics KW - structure AU - Sonego, Paolo AU - Kocsor, Andras AU - Pongor, Sandor PY - 2008/01/11/ UR - http://dx.doi.org/10.1093/bib/bbm064 ER -

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