Dr. Han Liang
The University of Texas MD Anderson Cancer Center
Department of Bioinformatics and Computational Biology
The fundamental question driving our research paradigm is how to take full advantage of cancer genomic data to elucidate the molecular basis of human cancer and develop effective prognostic and therapeutic strategies, thereby contributing to the true promise of personalized or precision cancer therapy.
Combining both computational and experimental approaches, my group research focuses on the following areas. (i) Develop cutting-edge computational algorithms and bioinformatic tools for better analyzing cancer genomic data. Over the past years, we have developed several popular bioinformatics tools, including TCPA, SurvNet, BM-Map and PATHOME. (ii) Pan-cancer analyses using The Cancer Genome Atlas (TCGA) data. We have pioneered a series of comparative analyses across tumor types using TCGA data. The topics include assessment of clinical utility, gene co-expression networks, transcribed pseudogenes and copy number variations. (iii) Develop systems-biology approaches for inferring driver molecular events from next-generation sequencing data. We performed the first transcriptome analysis on gastric cancer and the first whole-exome sequencing on endometrial cancer. (iv) Investigate the functional role of RNA editing in cancer. We use both computational and experimental approaches to systematically characterize RNA editing events in human cancer.
Since my group was established in 2009, we have published 28 papers including those published in Nature, Cell, Nature Biotechnology, Nature Genetics, Nature Medicine, Nature Cell Biology, Nature Methods, Nature Communications, Cancer Discovery and Genome Research. In the last year, each student or postdoc in our group published at least one first-author paper in a Nature sister journal.