DEEPre: sequence-based enzyme EC number prediction by deep learning.

ABSTRACT:

Motivation

Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number.

Results

We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manually crafted featu

SUBMITTER: Li Y 

PROVIDER: S-EPMC6030869 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature