On the prediction of DNA-binding proteins only from primary sequences: A deep learning approach.

ABSTRACT: DNA-binding proteins play pivotal roles in alternative splicing, RNA editing, methylating and many other biological functions for both eukaryotic and prokaryotic proteomes. Predicting the functions of these proteins from primary amino acids sequences is becoming one of the major challenges in functional annotations of genomes. Traditional prediction methods often devote themselves to extracting physiochemical features from sequences but ignoring motif information and location information between motifs. Meanwhile, the small scale of data volumes and large noises in training data result in lower accuracy and reliability of predictions. In this paper, we propose a deep learning based method to identify DNA-binding proteins from primary sequences alone. It utilizes two stages of convolutional

SUBMITTER: Qu YH 

PROVIDER: S-EPMC5747425 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature