# Project 4 - Modeling Spatial and Temporal Gene Regulation using Deep Neural Networks

> **NIH NIH P20** · BROWN UNIVERSITY · 2021 · $377,378

## Abstract

SUMMARY
Drug development of neurological disease and cancer relies heavily on our understanding of gene regulation.
We know that thousands of regulatory factors in the DNA environment play a role in controlling gene expression.
However, how these factors regulate gene expression across spatially and temporally continues to remain
unclear. Testing all possible combinations, experimentally, will take an enormous amount of time and resources.
Therefore, there is an urgent need to develop data-driven methods to extract relevant patterns from the
experimental datasets. Existing deep learning-based studies can model the relationship between regulatory
signals and gene expression. However, they fail to capture the underlying spatial and temporal structure of the
data. Extracting this information is a challenging task that is critical to our understanding of how gene regulation
drives cell development. Our research study aims to model the spatiotemporal gene regulation computationally.
We will achieve this by integrating chromatin modification, three-dimensional interaction, regulatory signals, and
gene expression data using deep learning methods. We plan to integrate 3D genome organization data with the
existing regulatory element signals by using a graph-based neural network to predict gene expression. We will
also implement neural network-based unsupervised methods that leverage the temporal structure in the existing
gene expression and chromatin accessibility data to generate in silico gene expression measurements for new
time-points. Integrating genome-wide spatial organization information and using temporal information will
accurately highlight the factors related to gene regulation. By applying our methods to diseased and healthy cell
lines, we will be able to identify the differentiating factors potentially involved in gene misregulation.

## Key facts

- **NIH application ID:** 10271626
- **Project number:** 2P20GM109035-06
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Ritambhara Singh
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $377,378
- **Award type:** 2
- **Project period:** 2016-06-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10271626

## Citation

> US National Institutes of Health, RePORTER application 10271626, Project 4 - Modeling Spatial and Temporal Gene Regulation using Deep Neural Networks (2P20GM109035-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10271626. Licensed CC0.

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