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Psychiatric Gene Networks: Solving the Molecular Puzzle of Psychiatric Disorders (Collaborative R01)

Post Date

March 25th 2015

Application Due Date

June 29th 2015

Funding Opportunity Number

RFA-MH-16-310

CFDA Number(s)

93.242

Funding Instrument Type(s)

Grant

Funding Activity Categories

Health

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; Asian American Native American Pacific Islander Serving Institutions (AANAPISISs); 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); Non-domestic (non-U.S.) Entities (Foreign Organizations); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession.

Funding

  • Estimated Total Funding:

    $2000000

  • Award Range:

    $None - $None

Grant Description

The purpose of this Funding Opportunity Announcement (FOA) and the companion FOA is to solicit applications for computational and functional analysis of gene networks and complex pathways that confer susceptibility to severe mental illnesses. These studies should leverage existing diverse multi-scale datasets and apply a combination of cutting-edge bioinformatics, computational predictive modeling, and systems biology approaches to identify and begin to evaluate novel genetic factors and molecular networks underlying functional pathways relevant to psychiatric disorders to verify their relationship or causality with disease/disease risk.The computational model predictions should be further replicated through independent datasets and confirmed using biological measures from existing and/or new experimental data.

Contact Information


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