Ferhat Ay, Ph.D.
Associate Professor
Institute Leadership Asst. Prof. of Computational Biology, Center for Autoimmunity and Inflammation, Center for Cancer Immunotherapy
"We look beyond the linear sequence of DNA to understand how the three-dimensional folding of the genome influences disease risk and severity for autoimmune diseases and cancer."

Overview

Our research uses computational and statistical modeling to understand the genetic and epigenetic bases of gene regulation in the context of several important systemic, infectious, and immune-related diseases. We work on bringing systematic and unbiased approaches to help develop and test specific hypotheses in human genetics, molecular biology, and immunology. We are particularly interested in the analysis and modeling of the 3D genome organization from high-throughput chromatin conformation capture data to understand how changes in this 3D structure affect outcomes such as development, differentiation, and disease progression. Our lab develops broadly used computational methods based in statistics, graph theory, data mining, and machine learning for the analysis of high-throughput data sets. We also have ongoing interests in systems-level analysis and reconstruction of regulatory networks, inference of enhancer-promoter contacts, predictive models of gene expression, analysis of single-cell data, as well as integrative, comparative, and high-resolution analysis of chromosomes conformation data such as Hi-C and HiChIP.

Featured publications

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Lab Members

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Jun 23, 2020
Ferhat Ay, Ph.D.
Associate Professor Institute Leadership Asst. Prof. of Computational Biology, Center for Autoimmunity and Inflammation, Center for Cancer Immunotherapy

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From the lab

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