Zhang, Ke Associate Professor

Dr. Zhang's long-term goal is to decode genetic events and molecular interactions of biological processes, and rigorously represent the complex molecular behaviors with mathematical models. We use advanced high-throughput technology and robust stochastic models to obtain the systematic picture of a biological process. Multiple types of omics data, such as microarray, RNA-seq, ChIP-seq, lipidomics and proteomics are collected through innovative study designs in animals and humans, and are modeled for integrative analysis. Using embryonic mouse as a model system, one of our current focuses is to untangle the spatial and dynamic gene-gene interaction networks during heart development, and illustrate how environmental factors introduce adverse molecular changes and morphological defects. We are also investigating the transgenerational epigenetic variations carried from overweight mother to the offspring, and how the change of lifestyles would prevent childhood obesity.