1. Charge to Us What CS is on the shelf waiting to be used What are the Bio Challenges to CS What are biggest roadblocks What if you ignore this?

2. What Bio Needs From CS Large Data sets –Collect large –Assess quality –Publish (make accessible) Data Analysis Tools –New tools –Existing tools that “normals” can use –Predictive tools (e.g. …) Workflow Capture –Procedure DTDs (beyond NLM DTD) Structured abstract Protocol e.g. micro-array MIAME –Inventory tools Peer-review of tools. Integrating large datasets –Standards for data representation What’s a Gene? –Tools to compare datasets –Algorithms to detect patterns High dimensionality –Tool evaluation –Conceptual Modeling Analysis, Analysis, Analysis, –Image search Describe dynamics –PDE ++ –Process calculus? Visualization Electronic medical record. –Representation –Identity/privacy/… –Rick Satava: – active EMR

3. Roadblocks Structure –Dignify (silo, rewards) –Transitional Research is not a CS goal –Encourage 2x2 groups Curriculum –Problem is long-term –K-12 is critical –Teach BOTH bio and math –Training grants Summer schools for cross-fertilization Business Model –Ways to engage expensive people Publication process not working –Text + Data –Data publication rules –Reproducible Research Intellectual property

4. Recommendation: Form Committee To Drive Agenda Cross-agency Specific NIH recommendations to attack a grand challenge One Super Center / 2 years @ 20M$/y Leverage Government funding with Industry/Private funds Already have NIH success in NII, Visible Human, Visualization, … Work with a Med School for a modern Flexner-Report for Teaching, Research, and Delivery Summer training programs Remember K-12 Discuss these issues with Zerhouni