AI-powered Immune Cell Knowledge Graph (ICKG) with granular immune contexts enables immune program interpretation.

ABSTRACT: The widespread application of single-cell and spatial omics to models and patient samples has transformed immune cell profiling across physiological conditions. However, knowledge of immune cell states, functions, and gene regulation remains fragmented across publications, limiting our ability to synthesize insights and derive mechanistic understanding from the literature. To address this gap and facilitate literature integration, we constructed Immune Cell Knowledge Graphs (ICKGs)-four cell type-specific graphs derived from over 24,000 cancer immunotherapy-focused PubMed abstracts using large language models (LLMs) with "human verifiable" validation. Unlike conventional databases, which provide context-agnostic pathways, ICKGs capture directed, literature-supported relationships among gen

SUBMITTER: He S 

PROVIDER: S-EPMC12846910 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature