Classifying RNA-binding proteins based on electrostatic properties.

ABSTRACT: Protein structure can provide new insight into the biological function of a protein and can enable the design of better experiments to learn its biological roles. Moreover, deciphering the interactions of a protein with other molecules can contribute to the understanding of the protein's function within cellular processes. In this study, we apply a machine learning approach for classifying RNA-binding proteins based on their three-dimensional structures. The method is based on characterizing unique properties of electrostatic patches on the protein surface. Using an ensemble of general protein features and specific properties extracted from the electrostatic patches, we have trained a support vector machine (SVM) to distinguish RNA-binding proteins from other positively charged proteins th

SUBMITTER: Shazman S 

PROVIDER: S-EPMC2518515 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature