Public Health Relevance

The massive generation of molecular information in oncology will not in itself change cancer death rates. This highlights the need to transition from archiving and binning facts to building predictive models of disease that help patients. Probabilistic causal models with curated data will allow early detection markers and directed therapies as well as predicting outcomes. The Sage CCSB will enable this distributed model building, while training scientists, building interface tools, and linking models between sites.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA149237-04
Application #
8567621
Study Section
Special Emphasis Panel (ZCA1-SRLB-C)
Project Start
2013-03-18
Project End
2014-02-28
Budget Start
2013-03-18
Budget End
2014-02-28
Support Year
4
Fiscal Year
2013
Total Cost
$2,124,509
Indirect Cost
$798,935
Name
Sage Bionetworks
Department
Type
DUNS #
830977117
City
Seattle
State
WA
Country
United States
Zip Code
98109
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