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OMICS Technologies For Predictive Modeling of Infectious Diseases (U19)

Post Date

June 8th 2012

Application Due Date

October 8th 2012

Funding Opportunity Number

RFA-AI-12-027

CFDA Number(s)

93.855
93.856

Funding Instrument Type(s)

Cooperative Agreement

Funding Activity Categories

Health

Number of Awards

4

Eligibility Categories

State Governments
County Governments
City or Township Governments
Special District Governments
Independent School Districts
Public and State Controlled Institutions of Higher Education
Federally Recognized Native American Tribal Governments
Public Housing Authorities or Indian Housing Authorities
Non-Federally Recognized Native American Tribal Organizations
Non-Profits With 501 (c) (3) Status With The IRS (Except Higher Education Institutions)
Non-Profits Without 501 (c) (3) Status With The IRS (Except Higher Education Institutions)
Private Institutions of Higher Education
For-Profit Organizations (Except Small Businesses)
Small Businesses
Other

Other Eligible Applicants include the following: Alaska Native and Native Hawaiian Serving Institutions; Eligible Agencies of the Federal Government; Faith-based or Community-based Organizations; Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Indian/Native American Tribal Governments (Other than Federally Recognized); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession; Non-domestic (non-U.S.) Entities (Foreign Institutions) are eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are eligible to apply. Foreign components, as defined in the NIH Grants Policy Statement, are allowed.

Funding

  • Estimated Total Funding:

    $13000000

  • Award Range:

    $None - $None

Grant Description

The purpose of this FOA is to develop and validate predictive models of infectious disease initiation, progression and outcomes. These models will be derived from the study of the architecture and dynamics of systems-wide host/pathogen molecular interaction networks during infection, using integrated datasets generated from a combination of omics technologies.

Contact Information


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