AI that reads detailed maps of genes and proteins in tumors
Machine learning methods for interpreting spatial multi-omics data
This project builds new AI tools to read detailed maps of genes, proteins, and tissue images to help understand breast tumors.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia Univ New York Morningside NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-11314480 on NIH RePORTER |
What this research studies
Researchers are creating advanced machine learning models that combine different lab measurements showing where genes and proteins sit inside tumor tissue and what the tissue looks like under a microscope. The tools will link spatial RNA measurements, protein signals, DNA-accessibility data (ATAC-seq), and copy-number changes to map neighborhoods of cells with shared states. They will use probabilistic and deep generative models to make these complex datasets easier to interpret and to infer how gene regulation varies across the tissue. The goal is to reveal patterns in the tumor microenvironment that could point to new diagnostic markers or treatment targets.
Who could benefit from this research
Good fit: Patients with breast cancer who can provide tumor tissue samples or consent to molecular profiling would be the ideal participants.
Not a fit: People with conditions unrelated to tumors or those who cannot or will not provide tissue samples are unlikely to benefit directly from this work.
Why it matters
Potential benefit: If successful, these tools could reveal how different parts of a tumor behave and point toward better diagnostics or more personalized treatments.
How similar studies have performed: Single-cell genomics methods have produced important insights, but combining spatial multi-omics (RNA, protein, ATAC, imaging) is newer and still being proven.
Where this research is happening
New York, United States
- Columbia Univ New York Morningside — New York, United States (Active)
Researchers
- Principal investigator: Azizi, Elham — Columbia Univ New York Morningside
- Study coordinator: Azizi, Elham
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.