Root-associated protein prediction using a protein large language model and hypergraph convolutional networks.

ABSTRACT: Plant root-associated proteins promote plant growth and enhance stress tolerance. They participate in signaling and plant growth regulation. It is clear that they play key roles in plant growth, development and environmental adaptation. At present, the root-associated proteins have not been fully discovered. It is essential to identify latent root-associated proteins. Traditional methods (proteomic analysis, transcriptome and expression analysis) for determining root-associated proteins are highly relied on the data generated by biochemical experiments, which are always expensive and time-consuming. On the other hand, the current computational models show weak ability, providing great spaces for improvement. In this study, we propose a new computational model, Hypergraph-Root, for predicti

SUBMITTER: Chen L 

PROVIDER: S-EPMC12873345 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature