Two-Level Protein Methylation Prediction using structure model-based features.

ABSTRACT: Protein methylation plays a vital role in cell processing. Many novel methods try to predict methylation sites from protein sequence by sequence information or predicted structural information, but none of them use protein tertiary structure information in prediction. In particular, most of them do not build models for predicting methylation types (mono-, di-, tri-methylation). To address these problems, we propose a novel method, Met-predictor, to predict methylation sites and methylation types using a support vector machine-based network. Met-predictor combines a variety of sequence-based features that are derived from protein sequences with structure model-based features, which are geometric information extracted from predicted protein tertiary structure models, and are firstly used in

SUBMITTER: Zheng W 

PROVIDER: S-EPMC7138832 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature