DeepSF: deep convolutional neural network for mapping protein sequences to folds.

ABSTRACT:

Motivation

Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a target protein based on the fold of a template protein with known structure, which cannot explain the relationship between sequence and fold. Only a few methods had been developed to classify protein sequences into a small number of folds due to methodological limitations, which are not generally useful in practice.

Results

We develop a deep 1D-convolution neural network (DeepSF) to directly classify any protein sequence into one of 1195 known folds, which is useful for both fold recognition and the study of sequence-structure relationship. Different from traditional se

SUBMITTER: Hou J 

PROVIDER: S-EPMC5905591 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature