DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction.

ABSTRACT:

Motivation

Automated function prediction (AFP) of proteins is a large-scale multi-label classification problem. Two limitations of most network-based methods for AFP are (i) a single model must be trained for each species and (ii) protein sequence information is totally ignored. These limitations cause weaker performance than sequence-based methods. Thus, the challenge is how to develop a powerful network-based method for AFP to overcome these limitations.

Results

We propose DeepGraphGO, an end-to-end, multispecies graph neural network-based method for AFP, which makes the most of both protein sequence and high-order protein network information. Our multispecies strategy allows one single model to be trained for all species, indicating a larger number of training samples tha

SUBMITTER: You R 

PROVIDER: S-EPMC8294856 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature