778-CellHermes: for Multimodal Omics Integration

Paper Talk · Apr 11, 2026 · 22m

CellHermes is a novel biological foundation model designed to unify diverse omics data by leveraging the reasoning power of pretrained large language models. Unlike traditional models trained from scratch on specific data types, this framework translates complex transcriptomic profiles and protein-protein interaction networks into a standardized natural language format. By reformulating biological datasets into question-answer pairs, the system emulates multiple self-supervised learning paradigms within a single, universal architecture. The model serves three primary functions: an encoder for…