Xiao Fan, Ph.D., Associate Research Scientist, Department of Systems Biology, Columbia University
Cardiomyopathy is a clinically and genetically heterogeneous form of heart muscle disease with substantial morbidity and mortality. Current guidelines recommend genetic testing in adults and children with hypertrophic, dilated, or restrictive cardiomyopathy. Robust data on clinical testing practices and diagnostic yield in children are lacking. In this talk, Dr. Xiao Fan will use participants enrolled in the Pediatric Cardiomyopathy Registry to estimate the percentage of genetically explainable cases. What do negative genetic findings mean? What can we learn from the negative findings? In the first part of the talk, novel risk genes are explored for pediatric cardiomyopathy. In the second part, deep learning methods are introduced to provide an improved prediction and greater detail about variant pathogenicity.
Biography: Dr. Xiao Fan is an associate research scientist in the Department of Systems Biology at the Columbia University. She completed her Ph.D. in Bioinformatics program at the University of Alberta in 2016. Her research interests involve studying genetic architecture of rare diseases using whole genome/exome sequencing data, improving genetic variant interpretation and using machine learning methods to answer medical/biochemical questions. She has published 24 journal articles and was a principal investigator of the NIH K99/R00 award in 2021.
Dr. Edward Phelps