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Briefings in Bioinformatics Advance Access first published online on January 11, 2008
This version published online on January 18, 2008
Briefings in Bioinformatics, doi:10.1093/bib/bbm064
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© The Author 2008. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

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

Paolo Sonego, András Kocsor and Sándor Pongor

Corresponding author. Sándor Pongor, Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34012 Trieste, Italy. Tel: +39-040 375 7300; Fax: +39-040 226 555; E-mail: pongor{at}icgeb.org

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.

Keywords: protein similarity searching, classification, ROC analysis, performance assessment, function prediction

András Kocsor's affiliation has been updated.

Submitted: October 25, 2007. Received (in revised form): December 18, 2007.


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