Lerner Research Institute News

Read about the latest advances from Lerner Research Institute scientists, including new findings, grant awards, innovations and collaborations.

Computational Biologist Dr. Ming Hu Receives $2.4M NIH Genomic Innovator Award

Dr. Hu is one of 11 researchers across the country to receive the prestigious grant for early-career genomics researchers.


The National Human Genome Research Institute (NHGRI) has awarded Department of Quantitative Health Sciences researcher Ming Hu, PhD, a five-year, $2.4 million grant to study how chromatin is organized within cells and its implications for human health and disease.

The grant is part of NHGRI’s Genomic Innovator Award program, which recognizes and supports early-career researchers in the field of genomics. Dr. Hu is one of 11 Genomic Innovator Award recipients named in 2021.

Research supported by this award will build on findings recently published in Nature Methods by Dr. Hu’s team and collaborations from the Center for Integrated Multi-Model and Multi-Scale Nucleome Research, which brings together an international team of genomics researchers and is also funded by the National Institutes of Health.

Combining single-cell genomics technologies, computational approaches to conquer human disease

Chromatin is the material within chromosomes that contain DNA and proteins. This genetic material is packed into a very small cellular compartment called the nucleus. The tight order and spatial organization of nuclear DNA helps to control which genes are turned on or off in specific cell types, while abnormal organization can cause gene dysregulation and a broad range of human diseases.

Dr. Hu and his collaborators developed a computational method called SnapHiC that can better characterize chromatin spatial organization in single cells than existing methods, even when studying complex human tissue samples. Now Dr. Hu will expand this line of investigation and study further how cell-type-specific gene regulation is governed by nuclear DNA organization. Ultimately, he hopes to identify novel genes directly associated with disease risk.

“We will develop and utilize statistical modeling and machine learning approaches to integrate single-cell multi-omics data in order to better understand the functional effects of chromatin spatial organization on gene expression,” said Dr. Hu. “By harnessing the power of cutting-edge single-cell genomics technologies and innovative computational approaches, we are able to characterize genome-wide chromatin interactions at single-cell resolution. Our team plans to make these computational methodologies widely available to other researchers to enable and speed the discovery of novel genes involved in various diseases.”

Image: Artistic rendering of genetic material tightly packaged in a cell's nucleus

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