Learning Interpretable Tumor Microenvironment Representations by Fitting Pan-Cancer Cell State-Niche Correlation

arXiv:2608.26208 · q-bio.GN · Submitted 2026-08-26 · Read on arXiv

q-bio.GN

Submitted: 2026-08-26

Updated: 2026-09-26

Code: https://github.com/lugia-xiao/GITIII_scale

Terminology

• Foundation Model — 27× in this paper · explained in 3 episodes
• Transformer — 21× in this paper · explained in 2 episodes
• Embeddings — 16× in this paper · explained in 2 episodes
• Foundation Models — 16× in this paper · explained in 7 episodes
• Interpretability — 10× in this paper · explained in 15 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Representation Learning — 4× in this paper · explained in 2 episodes
• Tokenization — 4× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 3 episodes
• Graph Construction — 3× in this paper · explained in 3 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Additivity — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data

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