My lab uses computational approaches to study the genetics of human diseases. A primary focus of our research is to develop novel tools for mapping risk genes of complex diseases from genome wide association studies (GWAS) and sequencing studies. These tools are often been used in close collaboration with experimental biologists. A key feature of our strategy is the integration of multiple genomic datasets, such as transcriptome data, epigenetic data, and biological networks. This integrated approach could combine signals in different datasets to increase the power of studies, and shed light on the mechanism connecting genetic changes to phenotypes.
We are also interested in computational questions in regulatory genomics. How do cis-regulatory sequences interpret the information in cellular environments to drive spatial-temporal gene expression patterns? How do variations of regulatory sequences shape phenotypic variation and evolution? We believe a better understanding of these questions will also help the study of human genetics, specifically by improving our ability to interpret variations in non-coding sequences.
Xin He, PhD
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Associate Professor of Human Genetics
Associate Professor of Neuroscience Institute
Committee on Cancer Biology
Committee on Genetics, Genomics and Systems Biology - Research and Scholarly Interests: Cancer genomics, Computational biology, Gene regulation, Psychiatric genetics, Statistical genetics
- Websites: Lab website, Research Network Profile
- Contact: xinhe@uchicago.edu
- Graduate Programs: Cancer Biology, Genetics, Genomics & Systems Biology, Human Genetics, UChicago Biosciences