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Related Experiment Video

Updated: Jan 31, 2026

Isolation and Characterization of the Immune Cells from Micro-dissected Mouse Choroid Plexuses

Isolation and Characterization of the Immune Cells from Micro-dissected Mouse Choroid Plexuses

Published on: February 3, 2022

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

Shan He¹, Yukun Tan¹, Qing Ye¹

¹Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX USA.

NPJ Artificial Intelligence

|January 30, 2026

Summary

We created Immune Cell Knowledge Graphs (ICKGs) from scientific literature to integrate fragmented immune cell knowledge. These graphs provide context-aware insights for immune cell function and gene regulation in omics research.

Keywords:

Complex networks Computational models Computational platforms and environments Computational science Computer science

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Last Updated: Jan 31, 2026

Isolation and Characterization of the Immune Cells from Micro-dissected Mouse Choroid Plexuses

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Published on: February 3, 2022

Studying Organelle Dynamics in B Cells During Immune Synapse Formation

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Published on: June 1, 2019

Isolation of Functional Cardiac Immune Cells

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Published on: December 5, 2011

Area of Science:

Immunology and Computational Biology
Leveraging advanced computational methods for biological data analysis
Integrating multi-omics data for immune system research

Background:

Single-cell and spatial omics have advanced immune cell profiling but knowledge remains fragmented.
Synthesizing immune cell states, functions, and gene regulation from literature is challenging.
Existing databases lack context-aware relationships crucial for mechanistic understanding.

Purpose of the Study:

To construct Immune Cell Knowledge Graphs (ICKGs) for integrating fragmented immune cell knowledge.
To enable context-aware reasoning about immune cell functions and gene regulation.
To facilitate mechanistic hypothesis generation in immune omics research.

Main Methods:

Utilized large language models (LLMs) to process over 24,000 PubMed abstracts focused on cancer immunotherapy.
Developed four cell type-specific knowledge graphs with human-verifiable validation.
Validated ICKGs against perturbation datasets from cytokine stimulation and CRISPR experiments.

Main Results:

ICKGs capture directed, literature-supported relationships among genes, pathways, and immune functions.
ICKGs provide more accurate and immunologically coherent contexts than canonical databases.
Identified interpretable pathway annotations, including novel signatures for immuno-oncology.

Conclusions:

ICKGs offer a scalable framework for functional interpretation in immune omics.
The developed interactive portal enables community access to ICKG-based pathway annotations.
This work enhances mechanistic hypothesis generation by integrating literature-derived immune cell knowledge.