Quantitative Systems Biotechnology  (QSB)  

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PROGRAM GUIDELINES

Solicitation  04-516

Important Notice to Proposers

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG), NSF 13-1, was issued on October 4, 2012 and is effective for proposals submitted, or due, on or after January 14, 2013. Please be advised that, depending on the specified due date, the guidelines contained in NSF 13-1 may apply to proposals submitted in response to this funding opportunity.

Please be aware that significant changes have been made to the PAPPG to implement revised merit review criteria based on the National Science Board (NSB) report, National Science Foundation's Merit Review Criteria: Review and Revisions. While the two merit review criteria remain unchanged (Intellectual Merit and Broader Impacts), guidance has been provided to clarify and improve the function of the criteria. Changes will affect the project summary and project description sections of proposals. Annual and final reports also will be affected.

A by-chapter summary of this and other significant changes is provided at the beginning of both the Grant Proposal Guide and the Award & Administration Guide.

DUE DATES

Archived

SYNOPSIS

As a result of recent advances in genomic and biochemical analysis, informatics, mathematics, and the engineering disciplines, it is now possible to approach an understanding of the integrated processes which translate the information contained in the genome into functioning biological entities.  Systems engineering approaches will be essential for characterizing the emergence of biological phenotypes from underlying hierarchies of interactions and environmental influences.  Understanding the quantitative systems behavior of cellular systems is important in its own right as well as providing a conceptual basis for biotechnological process development.

This Quantitative Systems Biotechnology solicitation seeks innovative high-risk/high-return proposals, which combine in-depth analysis of large-scale cellular biological systems, or their representations, with creative software tools for the development of computer models as well as complementary quantitative experimental approaches.  Multidisciplinary proposals are encouraged.