Rongkun Shen, Ph.D
Office: Lennon Hall B27
My research area is bioinformatics and computational biology. My goal is to understand how gene expression is regulated during development, by environmental stimulation, or in diseases in a genome-wide scale. The major approach is to apply computational and statistical methods to dicpher next generation sequencing data from those experiments.
My long-term goal is to understand genetic and epigenetic regulatory networks. The rapid advancement of DNA sequencing technology in recent years makes it possible to interrogate the gene regulation networks in a much quicker and deeper way. We focus on analyzing the next generation high-throughput sequencing data, including RNA-Seq, and ChIP-Seq from various projects to answer the specific biological questions. In addition, the current specific aims of my lab are: (1) microRNA target prediction using machine learing; (2) the differential binding of CREB and its mechanisms; and (3) integrative genomic data mining using supervised or semi-supervised learning approaches.