Yufeng Shen

Yufeng Shen


Assistant Professor, Department of Systems Biology
Associate Director, Columbia Genome Center


Department of Systems Biology
Center for Computational Biology and Bioinformatics
JP Sulzberger Columbia Genome Center
Department of Biomedical Informatics


(212) 851-4662

Yufeng Shen is an assistant professor in the Columbia University Department of Systems Biology and Department of Biomedical Informatics. After completing his PhD in computational biology in 2007 at the Human Genome Sequencing Center at Baylor College of Medicine, he led the analysis of the first personal genome produced by next-generation sequencing (that of Dr. James D. Watson). In 2008 he joined Columbia University as a postdoctoral fellow, working in computational genomics and genetics of drug adverse reactions, and then joined the faculty in July 2011. Dr. Shen is interested in developing and applying computational methods to study human genetics and diseases. The research in his group is at the interface of biology, statistics, and computer science. Specifically, his group is working in four areas, including genome sequencing and assembly, mapping of disease genes, the role of the major histocompatibility complex (MHC) in autoimmunity, and pharmacogenomics.

More News


DAMAGES: A Method for Predicting Rare Disease Risk Genes
Looking for distinctive gene expression patterns in different brain cell types offers a more efficient way to search for genetic alterations implicated in autism and reveals a molecular signature of the disorder.
Scientists Quantify Genetic Connections between Cancer and Developmental Disorders
A study led by Yufeng Shen suggests that cancer data could be used to pinpoint rare, damaging genetic alterations that increase the risk of developmental syndromes like autism.
Graduate Course Focuses on Foundations of Deep Sequencing
The new team-taught course provides an understanding of both the experimental principles of next-generation sequencing technologies and key statistical methods for analyzing the data they produce.
Mechanism of Kidney Transplant Tolerance Discovered
A new statistical approach for tracking expansion of rare T cell clones developed in Yufeng Shen's lab could make it possible to predict transplant rejection and provide evidence to guide the use of immuno- suppressive drugs.
Improving Single-Cell RNA-Seq at the Columbia Genome Center
Using the Fluidigm C1 System, Columbia researchers are developing methods for addressing the technical challenges of single-cell sequencing, and have begun generating some exciting data.