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Division of Biological Infrastructure

Innovations in Biological Imaging and Visualization  (IBIV)

CONTACTS

Name Email Phone Room
Timothy  Collins BIO-IBIV@nsf.gov 703 292-4763   
Richard  Rodewald BIO-IBIV@nsf.gov 703 292-7131   
Kamal  Shukla BIO-IBIV@nsf.gov 703 292-7131   

PROGRAM GUIDELINES

Solicitation  10-538

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

Current but no Longer Receiving Proposals

SYNOPSIS

The IBIV activity supports the development of novel approaches to the analysis of biological research images through the innovative "Ideas Lab" project development and review process.  The analysis and visual representation of complex biological images present daunting challenges across all scales of investigation, from multispectral analysis of foliage or algal bloom patterns in satellite images, to automated specimen classification, and tomographic reconstructions in structural biology.  Analysis of biological image data is complicated by a host of factors, including: complicated signal to noise profiles; variable feature size, density, scale, and perspective in images; experiment-specific metadata considerations; and reliance on subjective classification criteria.   Advances in biological image analyses have the potential to facilitate the automation of analytic processes, improve synthetic approaches to the analysis of large or heterogeneous data collections, and permit higher-order dimensional analyses of complex research models.  The goal of this activity is to identify opportunities for investment to advance the state-of-the-art in biological image analysis, data visualization, archiving, and dissemination.  Participants selected through an open application process will engage in an intensive five-day residential workshop to generate project ideas through an innovative, real-time review process.  Members of the biological research community, computational theorists and engineers, mathematicians, imaging specialists from other fields, educators involved in training the next generation of researchers, and a range of other specialists (artists, illustrators, etc.) are all strongly encouraged to participate.

THIS PROGRAM IS PART OF

Current Activities: no longer receiving proposals - DBI

Current Activities: no longer receiving proposals - DEB

Current Activities: no longer receiving proposals - EF

Current Activities: no longer receiving proposals - MCB


What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)

Map of Recent Awards Made Through This Program

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