Zhengqing Ouyang: Model-based embedding for 3D structure reconstruction

Living cells are composed of numerous macromolecules that form various shapes that are dynamically changing across cell states and types. Elucidating their 3D configurations are crucial for understanding the roles of macromolecules in heath and disease. However, traditional approaches are hindered by limitations in experimental or computational resources. We introduce a model-based embedding approach for 3D structure reconstruction that leverages high-throughput proximity ligation sequencing data. This approach efficiently models the noisy and sparse data and can be applied to major types of macromolecules.