# Computational modeling of spatial genome organization and gene regulation

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA RIVERSIDE · 2020 · $378,309

## Abstract

PROJECT SUMMARY/ABSTRACT
The three-dimensional (3D) organization of the genome plays an essential role in genome stability, gene regulation,
and many diseases, including cancer. The recent development of high-throughput chromatin conformation capture
(Hi-C) and its variants provide an unprecedented opportunity to investigate higher-order chromatin organization.
Despite the rapidly accumulating resources for investigating 3D genome organization, our understanding of the
regulatory mechanisms and functions of the genome organization remain largely incomplete. Hi-C analyses and
3D genome research are still in their early stage and face several challenges. First, high-resolution chromatin
contact maps require extremely deep sequencing and hence have been achieved only for a few cell lines. Second,
it is computationally challenging to complement 3D genome structure with one-dimensional (1D) genomic and
epigenomic features. Third, recent studies have just begun to infer associations between chromatin interactions
and genetic variants and to identify potential target genes of those variants at the genome-wide scale. Given
these challenges and my unique multi-disciplinary training, my long-term research goal is to develop innovative
computational and statistical methods to uncover the interplay between 3D genome structure and function.
Specifically, in the next five years, I will i) develop computational approaches to enhance the resolution of existing
Hi-C data and investigate fine-scale 3D genome architecture as well as its spatiotemporal dynamics and ii) build
scalable and interpretable machine learning models that leverage 1D epigenomic data to predict cell type-specific
3D chromatin interactions and gene expression and elucidate the function of 3D genome organization in gene
regulation and human diseases. The completion of the proposed work will deepen our knowledge of 3D genome
architecture as well as its functions in gene regulation and disease.

## Key facts

- **NIH application ID:** 9999005
- **Project number:** 5R35GM133678-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA RIVERSIDE
- **Principal Investigator:** Wenxiu Ma
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $378,309
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9999005

## Citation

> US National Institutes of Health, RePORTER application 9999005, Computational modeling of spatial genome organization and gene regulation (5R35GM133678-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9999005. Licensed CC0.

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