Goals

OHSU will lead the next generation of genomically guided therapies and early detection by discovering novel data-driven genotype/phenotype association inferred from large-scale analytics, and translating them to benefit clinical care. To enable this vision, the computational biology program will be guided by the following priorities:

• Demonstrate benefit to patients through advances in big data analytics
• Enable scientific goals of cross-departmental programs/projects
• Establish OHSU as a world leader in computational biology research

Strategies

In order to be an effective team we have implemented the following strategic goals:

• Move OHSU into the big data era through organizational structures, systems, and values fostering goal-directed team science
• Engage researchers to continuously build on work of colleagues around priority projects with high value-add across multiple basic science projects
• Initial build focus on integrative data analysis (including omics and imaging data) to predict disease phenotypes from clinical and genetic information
• Future build focus on early detection
• Develop strategic partnerships with world-leading efforts in priority areas

Objectives

The overall objectives for the team are as follows:

• Align existing efforts through standardization of tools and systems
• Build expertise in advanced probabilistic inference methods for integrative data analysis
• Build expertise in high-level, team oriented software development
• Create a transparent, accessible body of data inter-operable with large-scale public data sources
• Advance research goals across multiple basic science initiatives