Dr. Han Liang
The University of Texas MD Anderson Cancer Center
Department of Bioinformatics and Computational Biology
The overall goal of my research is to understand the genetic and molecular mechanisms of human cancers through the analysis and interpretation of high-throughput genomic data. We are also interested in developing novel computational methods and bioinformatic tools for such a purpose. In particular, we focus on integrative analysis of cancer genomic data and analysis of next-generation sequencing data. Other active research topics include microRNA regulation, network-based biology and comparative analysis of mammalian genomes.
The biomarkers for cancer are conventionally based on individual genes, and this practice often makes it hard to interpret the underlying mechanism. The availability of various biological networks, such as gene regulatory and protein interaction networks, has allowed us to use sub-network as biomarkers.
Somatic copy-number alterations (SCNAs) play a crucial role in the development of human cancers. Taking advantage of recently available SCNA data in many cancer types, we wonder what molecular and evolutionary mechanisms underlie the global SCNAs patterns in various cancer types and what genetic and epigenetic elements most correlate with SCNA occurrence.
Alternative splicing is a crucial regulatory mechanism for producing different protein products from the same gene locus, which is largely controlled by splicing sites. However, little is known about the adaptivity and plasticity of splicing regulation during the evolution of modern human populations. The goal of this project is to discover the splicing genes with population-specific adaptation through analyzing the 1000 Genome Project data.
Office: MDA FCT 4.5030 (Unit 1410)
Title: Assistant Professor
Ph.D. - Princeton University - 2006