Rama: a machine learning approach for ribosomal protein prediction in plants.

ABSTRACT: Ribosomal proteins (RPs) play a fundamental role within all type of cells, as they are major components of ribosomes, which are essential for translation of mRNAs. Furthermore, these proteins are involved in various physiological and pathological processes. The intrinsic biological relevance of RPs motivated advanced studies for the identification of unrevealed RPs. In this work, we propose a new computational method, termed Rama, for the prediction of RPs, based on machine learning techniques, with a particular interest in plants. To perform an effective classification, Rama uses a set of fundamental attributes of the amino acid side chains and applies a two-step procedure to classify proteins with unknown function as RPs. The evaluation of the resultant predictive models showed that Rama

SUBMITTER: Carvalho TFM 

PROVIDER: S-EPMC5701237 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature