Molecular Biology: Open Access

Jinghui Zhang

Jinghui Zhang
Computational Biology MS 1135, Room IA6038 St. Jude Children's Research Hospital 262 Danny Thomas Place Memphis.

Biography

I am a computational biologist interested in understanding the effect of genetic alterations on cancer initiation, progression and prognosis through integrative analysis of large-scale, multi-dimensional genomic data. My research interest has been in the development of highly accurate and sensitive computational methods for analyzing large-scale genomic data derived from high-throughput sequencing, especially in the area of genetic and epigenetic alterations in cancer genome. Early in my career, I participated in the development of the widely used BLAST algorithm and led the genetic variation analysis of the first assembled human genome. For the last 10 years I have been working very closely with experimental cancer genomics researchers, which has made me keenly aware of the consequences of analytical errors on downstream functional research.

Research Interest

To build a comprehensive error model for large-scale genomic analysis and developing cross-platform data integration methods have been my primary research interest. Development of visualization tools for viewing integrative genomic data is another key interest as these tools are indispensable for gaining understanding of the experimental data and for reviewing the accuracy of the computational results obtained from the astronomical volume of the genomic data generated with the current technology. By focusing on understanding genomic data error model, the tools we developed have contributed to the key discoveries made in the pilot phase of two major cancer genomic initiatives of the National Cancer Institute: Cancer Genome Atlas Project (TCGA) and the Therapeutically Applicable Research to Generate Effective Treatment (TARGET). Understanding the genetic and epigenetic landscape of pediatric cancer is currently the main focus of my research as my group leads the computational analysis of the next-generation sequencing data generated from the St. Jude Children’s Research Hospital - Washington University Pediatric Cancer Genome Project (PCGP). Developing novel approaches that integrate whole-genome sequencing data with RNA sequencing, copy number variation, structural variation, telomere content and gene expression is an ongoing effort. As of Jan. 2013, we have published key findings which unveil the genetic basis of several pediatric cancers including early T-cell precursor acute lymphoblastic leukaemia, retinoblastoma, medulloblastoma, neuroblastoma and high grade glioblastoma.