Grape-Pi: graph-based neural networks for enhanced protein identification in proteomics pipelines.

ABSTRACT:

Motivation

Protein identification via mass spectrometry (MS) is the primary method for untargeted protein detection. However, the identification process is challenging due to data complexity and the need to control false discovery rates (FDR) of protein identification. To address these challenges, we developed a graph neural network (GNN)-based model, Graph Neural Network using Protein-Protein Interaction for Enhancing Protein Identification (Grape-Pi), which is applicable to all proteomics pipelines. This model leverages protein-protein interaction (PPI) data and employs two types of message-passing layers to integrate evidence from both the target protein and its interactors, thereby improving identification accuracy.

Results

Grape-Pi achieved significant improvements in a

SUBMITTER: Gu C 

PROVIDER: S-EPMC12096076 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature