Efficient prediction of co-complexed proteins based on coevolution.

ABSTRACT: The prediction of the network of protein-protein interactions (PPI) of an organism is crucial for the understanding of biological processes and for the development of new drugs. Machine learning methods have been successfully applied to the prediction of PPI in yeast by the integration of multiple direct and indirect biological data sources. However, experimental data are not available for most organisms. We propose here an ensemble machine learning approach for the prediction of PPI that depends solely on features independent from experimental data. We developed new estimators of the coevolution between proteins and combined them in an ensemble learning procedure.We applied this method to a dataset of known co-complexed proteins in Escherichia coli and compared it to previously published

SUBMITTER: de Vienne DM 

PROVIDER: S-EPMC3494725 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature