Combining tissue-level and single-cell genetic data to map how cell types and signals change in disease
Integrative network modeling of bulk and single-cell sequencing data to characterize multi-scale cell architecture
['FUNDING_OTHER'] · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · NIH-11159642
This project uses detailed single-cell and broader tissue genetic data to build maps of how different cell types and their signals change in diseased tissues, helping conditions driven by altered cell communities.
Quick facts
| Phase | ['FUNDING_OTHER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI (nih funded) |
| Locations | 1 site (NEW YORK, UNITED STATES) |
| Trial ID | NIH-11159642 on ClinicalTrials.gov |
What this research studies
Researchers will merge high-depth bulk sequencing datasets with single-cell sequencing to capture both broad molecular signals and fine-grained cell-level detail. They will develop a new unsupervised clustering and network modeling tool (scRECIEM) to identify multi-scale cell populations and their signaling interactions in disease tissues. The team will use public clinical datasets and network biology methods to infer cell abundances and disease-related pathways across large patient cohorts. Findings aim to reveal cellular architectures and signaling changes linked to disease mechanisms and potential therapeutic targets.
Who could benefit from this research
Good fit: People with diseases that involve changes in tissue cell composition—such as cancers, inflammatory diseases, or fibrotic conditions—are the most relevant patients for the types of findings this project aims to generate.
Not a fit: Patients seeking immediate treatments or those with conditions unrelated to tissue-level cell changes are unlikely to directly benefit from this computational research in the short term.
Why it matters
Potential benefit: If successful, this work could identify disease-driving cell types and signaling pathways that guide better diagnostics and new treatment targets.
How similar studies have performed: Related efforts that combine bulk and single-cell data have shown promise in revealing cell populations and pathways, but this project introduces novel, unproven computational methods that require validation.
Where this research is happening
NEW YORK, UNITED STATES
- ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI — NEW YORK, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: SONG, WON-MIN — ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- Study coordinator: SONG, WON-MIN
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.