A fast SCOP fold classification system using content-based E-Predict algorithm.

ABSTRACT:

Background

Domain experts manually construct the Structural Classification of Protein (SCOP) database to categorize and compare protein structures. Even though using the SCOP database is believed to be more reliable than classification results from other methods, it is labor intensive. To mimic human classification processes, we develop an automatic SCOP fold classification system to assign possible known SCOP folds and recognize novel folds for newly-discovered proteins.

Results

With a sufficient amount of ground truth data, our system is able to assign the known folds for newly-discovered proteins in the latest SCOP v1.69 release with 92.17% accuracy. Our system also recognizes the novel folds with 89.27% accuracy using 10 fold cross validation. The average response time f

SUBMITTER: Chi PH 

PROVIDER: S-EPMC1579235 | biostudies-literature | 2006 Jul

REPOSITORIES: biostudies-literature