title: A Protein Classification Benchmark collection for machine learning.
abstract: Protein classification by machine learning algorithms is now widely used in structural and functional annotation of proteins. The Protein Classification Benchmark collection (http://hydra.icgeb.trieste.it/benchmark) was created in order to provide standard datasets on which the performance of machine learning methods can be compared. It is primarily meant for method developers and users interested in comparing methods under standardized conditions. The collection contains datasets of sequences and structures, and each set is subdivided into positive/negative, training/test sets in several ways. There is a total of 6405 classification tasks, 3297 on protein sequences, 3095 on protein structures and 10 on protein coding regions in DNA. Typical tasks include the classification of structural domains in the SCOP and CATH databases based on their sequences or structures, as well as various functional and taxonomic classification problems. In the case of hierarchical classification schemes, the classification tasks can be defined at various levels of the hierarchy (such as classes, folds, superfamilies, etc.). For each dataset there are distance matrices available that contain all vs. all comparison of the data, based on various sequence or structure comparison methods, as well as a set of classification performance measures computed with various classifier algorithms.
authors.affiliation: Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Padriciano 99, 34012 Trieste, Italy.
authors.forename: Paolo
authors.initials: P
authors.lastname: Sonego
authors.forename: Mircea
authors.initials: M
authors.lastname: Pacurar
authors.forename: Somdutta
authors.initials: S
authors.lastname: Dhir
authors.forename: Attila
authors.initials: A
authors.lastname: Kertész-Farkas
authors.forename: András
authors.initials: A
authors.lastname: Kocsor
authors.forename: Zoltán
authors.initials: Z
authors.lastname: Gáspári
authors.forename: Jack A M
authors.initials: JA
authors.lastname: Leunissen
authors.forename: Sándor
authors.initials: S
authors.lastname: Pongor
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D030562:Databases, Protein; D020407:Internet; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry / Q000145:classification*; D015203:Reproducibility of Results; D020539:Sequence Analysis, Protein; D014584:User-Computer Interface
chemical_list: D011506:Proteins