title: ROC analysis: applications to the classification of biological sequences and 3D structures.
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.
authors.affiliation: Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34012 Trieste, Italy.
authors.forename: Paolo
authors.initials: P
authors.lastname: Sonego
authors.forename: András
authors.initials: A
authors.lastname: Kocsor
authors.forename: Sándor
authors.initials: S
authors.lastname: Pongor
mesh_terms: D000465:Algorithms; D008956:Models, Chemical; D008958:Models, Molecular; D008968:Molecular Conformation; D012372:ROC Curve; D016415:Sequence Alignment / Q000379:methods*; D017421:Sequence Analysis / Q000379:methods*; D012984:Software