MEGA-GO: functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network.

ABSTRACT:

Motivation

The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models have emerged as a promising solution to expedite the annotation process. However, despite making significant progress in protein research, graph neural networks face challenges in capturing long-range structural correlations and identifying critical residues in protein graphs. Furthermore, existing models have limitations in effectively predicting the function of newly sequenced proteins that are not included in protein interaction networks. This highlights the need for novel approaches integrating protein structure and sequence data.

Re

SUBMITTER: Lee Y 

PROVIDER: S-EPMC11810639 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature