COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator.

ABSTRACT:

Background

The post-genomic era with its wealth of sequences gave rise to a broad range of protein residue-residue contact detecting methods. Although various coevolution methods such as PSICOV, DCA and plmDCA provide correct contact predictions, they do not completely overlap. Hence, new approaches and improvements of existing methods are needed to motivate further development and progress in the field. We present a new contact detecting method, COUSCOus, by combining the best shrinkage approach, the empirical Bayes covariance estimator and GLasso.

Results

Using the original PSICOV benchmark dataset, COUSCOus achieves mean accuracies of 0.74, 0.62 and 0.55 for the top L/10 predicted long, medium and short range contacts, respectively. In addition, COUSCOus attains mean area

SUBMITTER: Rawi R 

PROVIDER: S-EPMC5159955 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature