Opportunity ID: 240180

General Information

Document Type:: Grants Notice
Funding Opportunity Number:: RFA-RM-13-013
Funding Opportunity Title:: Library of Integrated Network-Based Cellular Signatures (LINCS): Perturbation-Induced Data and Signature Generation Centers (U54)
Opportunity Category:: Discretionary
Opportunity Category Explanation::
Funding Instrument Type::
Category of Funding Activity:: Health
Category Explanation::
Expected Number of Awards::
Assistance Listings Number(s):: 93.310 — Trans-NIH Research Support
Cost Sharing or Matching Requirement:: No
Version:: Synopsis 2
Posted Date:: Aug 19, 2013
Last Updated Date:: Aug 19, 2013
Original Closing Date for Applications:: Dec 19, 2013
Current Closing Date for Applications:: Dec 19, 2013
Archive Date:: Jan 19, 2014
Estimated Total Program Funding:: $ 10,000,000
Award Ceiling:: $1,700,000
Award Floor:: $

Eligibility

Eligible Applicants:: Small businesses
Additional Information on Eligibility:: 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); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession; Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply.
Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.
Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.

Additional Information

Agency Name:: National Institutes of Health
Description:: This FOA seeks to establish a large-scale data production effort to systematize approaches for identifying mechanism-based associations between the effects of disparate biological perturbations, by means of signatures. Such perturbations may include siRNAs, small bioactive molecules, environmental manipulations, among others. These data will also inform a knowledge base that can be used to study functional relationships among the responding cellular components. The Library of Integrated Network-Based Cellular Signatures (LINCS) program will support high-throughput collection and integrative computational analysis of informative molecular activity and cellular response features applied to a set of carefully selected human cell types. Relevant predictive patterns of molecular activities and other cellular behaviors are the cellular signatures that characterize responses to a variety of perturbing agents. The resulting knowledge-base of signatures will form the basis of a long-lived resource that can be used broadly by the community. For example, LINCS may inform the association of disease states with detailed molecular or cellular phenotypes caused by specific genetic variants, relating disease with changes in the function of specific gene networks, or the mechanism of action of known drugs. This FOA seeks to fund large-scale data production efforts that will enhance the existing LINCS resource while addressing the following: use of a broader range of cell types and assays than used in the existing LINCS resource, improved multidimensional data integration, some new technology development, user-interfaces needed by the typical biomedical scientist, and dissemination of the LINCS approach to study a broad range of disease biology and mechanisms. The outcomes of the research solicited by this FOA are expected to be highly synergistic with those of other research programs.
Link to Additional Information::
Grantor Contact Information:: If you have difficulty accessing the full announcement electronically, please contact:

Version History

Version Modification Description Updated Date
Synopsis 2 Modified to add Estimated Total Program Funding information. Aug 19, 2013
Synopsis 1

Package Status

Package No: 1

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