Proformer: a multimodal proteomics transformer model for multidisease early risk assessment.

ABSTRACT: Early identification of individuals at high risk for chronic diseases is crucial for prevention and intervention, yet current risk assessment tools are disease-specific, require extensive clinical data collection, and cannot provide multidisease risk profiles from a single measurement. Several protein large language models have been developed for tasks such as protein structure prediction, function prediction, and sequence design. However, none of these models can be directly applied in clinical settings to predict an individual's future disease risk. Here, we present a multimodal proteomics Transformer (Proformer) model that integrates protein expression, sequence, and function information for multidisease risk assessment. We trained Proformer using real proteomics data from 47 124 indivi

SUBMITTER: Qiu S 

PROVIDER: S-EPMC12743296 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature