Cancer Data Analysis

Cancer research has become increasingly data intensive. Understanding tumor biology depends on interpreting and leveraging vast data sets, both publicly available and internally generated. Such data analysis requires access to a dynamic suite of analytical tools; infrastructure supporting those tools; computational, bioinformatic and statistical expertise to mine and analyze the data; and quantitative analysts and software engineers to develop and build queries and algorithms. The Computational Sciences (CS) resource addresses faculty needs by providing in-depth expertise to JAXCC members in support of their independent research projects. This includes guidance in experimental design; support for the integration of multi-platform data sets, data analysis software applications and database development; development and application of computational procedures, statistical methods and scientific software; and project management.

Our Objective

Aim 1. To support JAXCC members in developing cutting-edge analytical procedures for emerging problems in cancer genomics, and to carry out integrative analysis in fundamental and translational cancer research.

Aim 2. To develop bioinformatics applications, maintain scientific analysis workflows, and provide data architecture and software engineering expertise for the development and management of scientific data portals pertaining to specific scientific questions addressed by JAXCC members.

Aim 3. To assist in resource planning for and management of complex computational projects and long-term information technology and data science development for JAXCC members.



CS is supported by NIH Grant No. P30 CA034196. These services are limited to Jackson Laboratory researchers and investigators only.