Our goal is to provide world-class analyses for institutional projects, such as the Pediatric Cancer Genome Project, large inter-departmental projects and genomic experiments for individual St. Jude investigators. Our projects range in scale and scope from the analysis of a single data type for one biospecimen to the design, integration and analysis of multiple data types in large cohorts. We handle genomic, transcriptomic, and epigenomic data from human, mouse, yeast, zebrafish, influenza, and bacterial genomes.
The Computational Biology Department has a diverse team of experienced bioinformatics scientists and talented software engineers. As a team, we are able provide the broad range of analytical and computational skills needed to provide high-quality analysis for complex next-generation data sets. The department develops and improves analytic methods and integrates complementary data from multiple assays.
Scientists who successfully led data analysis for the Pediatric Cancer Genome Project and the former Hartwell Center Bioinformatics group are now integrated into one department with five functional groups. Each group is a focused team with expertise in specific bioinformatics domains. While focused projects only require the attention of a single group, complex data exploration and integration frequently calls for the interaction of several groups. In addition to these multi-group teams, there are long-standing collaborations with the Biostatistics Department and proteomics group. These collaborations are intended to develop, improve and expand our library of analytical methods.
Department of Computational Biology
MS 1160, Room I6104
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
Genetic and epigenetic data integration by machine learning approaches
Genomic approaches to studying cis-regulatory modules in hematopoiesis
Cellular and genetic origins of childhood cancers
Systems biology, functional genomics and immuno-oncology
Genomic sequence analysis and visualization