The Department of Computational Biology develops innovative computational methods to answer challenging biological questions. We accomplish this through the seamless integration of dry-lab and wet-lab approaches.
The department is organized into four synergistic areas:
- Independent faculty research focused primarily on genomics and epigenetics; image analysis; and systems biology
- Collaborative multidisciplinary research supporting projects across St. Jude
- Wet-lab and computing technology development
- Clinical genomics for St. Jude clinical trials and patient care
Investigators collaborate extensively within the department and across basic research and clinical departments at St. Jude. Our faculty research interests range from cancer genomics to machine learning, single-cell sequencing and network construction.
Through our computational infrastructure, innovative analytical approaches and technology development we have accelerated progress in critical research areas. For example, analytical approaches and visualization tools we developed during the St. Jude – Washington University Pediatric Cancer Genome Project have led to discovery of novel mutations driving pediatric cancers.
Our bioinformatics approaches are now being used for many clinical applications, including cancer genetic predisposition studies and the development of targeted therapies. Some of these are being assessed in St. Jude-led pediatric clinical trials. To advance cures, we freely share data analysis software and visualization tools with the global scientific community.
Department of Computational Biology
MS 1135, Room IA6038
St. Jude Children's Research Hospital
262 Danny Thomas Place
Memphis, TN 38105-3678
Phone: (901) 595-7069
Fax: (901) 595-7100
Preferred contact method: email
OMICS integration and tumor heterogeneity by machine learning approaches
Genomic approaches to studying cis-regulatory modules in hematopoiesis
Cellular and genetic origins of childhood cancers
Genetic epidemiology of pediatric cancer and survivorship
Systems biology, functional genomics and immuno-oncology
Genomic sequence analysis and visualization