A Protein Classification Benchmark collection for machine learning.
Ontology highlight
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 d
SUBMITTER: Sonego P
PROVIDER: S-EPMC1669728 | biostudies-literature | 2007 Jan
REPOSITORIES: biostudies-literature
ACCESS DATA