# Revealing cell-level gene regulation through integration of single-cell multi-omics measurements

> **NIH NIH R35** · TRUSTEES OF INDIANA UNIVERSITY · 2022 · $378,279

## Abstract

Summary
Advanced single-cell sequencing techniques have enabled us to infer gene regulation at the single-cell level. We
propose to develop computational methods to overcome obstacles for elucidating gene regulation at single-cell
resolution. We first present an alignment-based computational framework to integrate single-cell multi-omics
measurements. The alignment-based computational framework can effectively handle the cell type imbalance
problem and is more robust to hyperparameters. Furthermore, we incorporate the integrated single-cell multi-omics
measurements and advanced machine learning algorithms to infer transcriptional regulation, distal regulatory
elements, and post-transcriptional regulation at the single-cell level. We expect to develop computational methods
to better understand gene regulation, which would lay a solid foundation for disease diagnosis, treatment, and
prevention.

## Key facts

- **NIH application ID:** 10500522
- **Project number:** 1R35GM147241-01
- **Recipient organization:** TRUSTEES OF INDIANA UNIVERSITY
- **Principal Investigator:** Yijie Wang
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $378,279
- **Award type:** 1
- **Project period:** 2022-09-26 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10500522

## Citation

> US National Institutes of Health, RePORTER application 10500522, Revealing cell-level gene regulation through integration of single-cell multi-omics measurements (1R35GM147241-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10500522. Licensed CC0.

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