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This section will focus on applying novel technologies to access gene regulation networks, understand complex disease mechanism, and deep learning approaches for sequencing data analysis and rare variant interpretation.
Learning Objectives:
1. State the advantages of multimodal single cell sequencing in defining CRISPR induced genetic variation.
2. Identify the gene regulatory mechanisms downstream of neuron-astrocyte interactions.
3. Evaluate the relationship between circRNA function and Alzheimer's disease.
4. Construct an in silico module for comprehensive gene regulatory networks analyses.
5. Design novel methods and deep learning approaches for sequencing data analysis.
6. Define a new approach to interpret rare variants when the goal is to identify a sub-population at low risk of disease
Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

Jonathan Berg, MD, PhD (Moderator)
Professor, Department of Genetics
UNC Chapel Hill

Yuxin Fan, MD, PhD (Moderator)
Associate Professor
Baylor College of Medicine

Yuriy Baglaenko, PhD
Principal Investigator at Baglaenko Lab
Cincinnati Children's Hospital Medical Center

Boxun Li, PhD
Postdoctoral Associate
Gersbach Lab

Feng Wang, PhD
Assistant Academic Research Scientist
Bing Yao Lab
Zechuan Shi
PhD Candidate
University of California, Irvine
Siying Yang, Master of Science
Graduate Student at Harvard Medical School, Biomedical Informatics
Research Assistant at Dr. Heng Li Lab, Dana Farber Cancer Institute
