Departmental Focus
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.
Contact Us
Department of Computational Biology
MS 1135, Room IA6038
St. Jude Children's Research Hospital
262 Danny Thomas Place
Memphis, TN 38105-3678
Email: jinghui.zhang@stjude.org
Phone: (901) 595-7069
Fax: (901) 595-7100
Preferred contact method: email
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Brian J. Abraham, PhD
Abraham
Transcriptional control of cell identity and disease
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Xiang Chen, PhD
Chen
OMICS integration and tumor heterogeneity by machine learning approaches
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Yong Cheng, PhD
Cheng
Genomic approaches to studying cis-regulatory modules in hematopoiesis
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Paul Geeleher, PhD
Geeleher
Computational methods and drug repositioning
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Mathematical modeling of cancer initiating events
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Zhaoming Wang, PhD
Wang
Genetic epidemiology of pediatric cancer and survivorship
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Systems biology, functional genomics and immuno-oncology
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Jinghui Zhang, PhD
Zhang
Genomic sequence analysis and visualization
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Xin Zhou, PhD
Zhou
Multi-omics and biomedical data visualization
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Neil Hayes, MD, MS, MPH
Hayes
Methodological approaches to the classification of cancer
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