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Investigator Initiated Research in Computational Genomics and Data Science (R01 Clinical Trial Not Allowed)

HHS-NIH11

Status:

Active

July 29, 2021

Posted:

Deadline: 

September 7, 2024

Funding

Program:

Award Floor:

Ceiling:

Match Required?

No

Eligibility

All

States:

Entity Types:

State governments, County governments, City or township governments, Special district governments, Independent school districts, Public & State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities, Native American tribal organizations, Nonprofits (with 501(c)(3) status), Nonprofits (without 501(c)(3) status)

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.

Contact

Email:

Phone:

Source Type:

Federal

The purpose of this funding opportunity announcement (FOA) is to invite applications for a broad range of research efforts in computational genomics, data science, statistics, and bioinformatics relevant to one or both of basic or clinical genomic science, and broadly applicable to human health and disease. This FOA supports fundamental genomics research developing innovative analytical methodologies and approaches, early-stage development of tools and software, and refinement or hardening of software and tools of high value to the biomedical genomics community. Work supported under this FOA should be enabling for genomics and be generalizable or broadly applicable across diseases and biological systems. All applications should address how the methods would scale to address increasingly larger data sets.

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