The Jiang lab website: https://sites.google.com/view/jiang-lab/
My research is centered on developing statistical methods and data-driven approaches to leverage massive genomic and transcriptomic data to investigate the temporal-spatial variation and dynamics of gene regulation, understanding and tackling the heterogeneity of cellular populations, complex traits and diseases. One unique aspect of my research is that I integrate a variety of statistical/bioinformatic methods, such as network modeling, machine learning, and genomic and transcriptomic data analysis, to leverage complex/large-scale omics datasets. These integrative computational approaches allow us to maximize the knowledge learned from the data to gain novel insights into the fundamental and translational aspects of human diseases. Another unique aspect of my research is that I have developed several comparative genomic strategies that allow us to analyze high-throughput sequencing data generated from species lacking sequenced genomes or with poorly annotated genes, such as Nile grass rat.