Shen Lab Research

Our lab at Columbia University studies human biology and diseases using genomic and computational approaches. We are developing new methods to identify genetic causes of human diseases and to understand the dynamics of adaptive immune system. Our research is at the interface of computer science, statistics, biology, and medicine. We work in three areas:

Computational genomics     |     Human genetics     |     Computational immunology

Computational Genomics

We develop new computational methods to interpret human genomes with machine learning models and large-scale population data. Ongoing projects: predict functional and fitness effect of missense and noncoding variants using deep learning and graphical models, joint analysis of single cell functional genomics data and genetic data in risk gene discovery, and automated methods to identify structural variants from exome or genome sequencing data in biobank-scale studies. Representative papers:

Human Genetics

Identification of genetic causes of human diseases provides the foundation for precise diagnosis and risk prediction, understanding of disease mechanisms, and rational search of targets for intervention. We apply computational and statistical methods in genetic studies of a broad range of human diseases and conditions. Recently we have been working on autism, congenital diaphragmatic hernia, congenital heart disease, pulmonary hypertension, tracheoesophageal defects, and breast cancer. Representative papers:

Computational Immunology

Computational analysis and mathematical modeling to understand dynamics of immune cells in human. We are interested in predictive and generative models of T cell receptor recognition of antigens, the transcriptomic and clonal dynamics of T cells in development, vaccine response, viral infections, and organ transplantation. Representative papers:

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