Research Goals

1. Integrating Deep Learning and Single-Molecule Sequencing for rapid multiomics
My research leverages deep learning to decode the complex information captured by single-molecule sequencing technologies. By integrating this flavor of data with deep learning, I aim to build predictive models that can assist both researchers and clinicians in understanding genomic diseases.

Integrating Single-Molecule Sequencing and Deep Learning to Predict Haplotype-Specific 3D Chromatin Organization in a Mendelian Condition.     Dubocanin D,  … Altemose N.  bioRxiv (2025). 

2. Single-Molecule analysis of the regulatory genome
I focus on developing approaches to probe the fundamental mechanisms underlying genome maintenance and regulation in health and disease. These tools enable measurements of chromatin dynamics, DNA-protein interactions, and the structural changes underlying crucial genomic processes. 

A telomere-to-telomere map of somatic mutation burden and functional impact in cancer. Sohn M-H*, Dubocanin D*,... Stergachis AB. bioRxiv (2025).

3. Uncovering Function and Regulation of Repetitive DNA and the "Dark Genome"
Repetitive DNA and other poorly characterized regions of the genome, often referred to as the "dark genome," represent a vast and under-explored genomic frontier. I work on understanding the roles these elements play in genome organization, gene regulation, and genome stability. I aim to unravel the sequence complexity and understand the layered regulatory mechanisms within these regions. 

Conservation of dichromatin organization along regional centromeres.  Dubocanin D, … Stergachis AB. Cell Genomics (2025).

Single-molecule architecture and heterogeneity of human telomeric DNA and chromatin. Dubocanin D, … Stergachis AB bioRxiv (2022).