
NSF Org: |
CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems |
Recipient: |
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Initial Amendment Date: | December 2, 2009 |
Latest Amendment Date: | December 2, 2009 |
Award Number: | 0954578 |
Award Instrument: | Standard Grant |
Program Manager: |
Leon Esterowitz
CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems ENG Directorate for Engineering |
Start Date: | January 1, 2010 |
End Date: | August 31, 2016 (Estimated) |
Total Intended Award Amount: | $400,518.00 |
Total Awarded Amount to Date: | $400,518.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
926 DALNEY ST NW ATLANTA GA US 30318-6395 (404)894-4819 |
Sponsor Congressional District: |
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Primary Place of Performance: |
225 NORTH AVE NW ATLANTA GA US 30332-0002 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | BioP-Biophotonics |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.041 |
ABSTRACT
0954578
Lu
The long-term objective is to develop and use powerful microfluidic and automation tools to understand genetic pathways that regulate the biochemical communications between neurons and other tissues in C. elegans. Microfluidics is ideal for studies of small organisms such as C. elegans because of the relevant length scales and the possibility of integration and automation. The research objective of the CAREER project is to engineer a microfluidic system for live imaging of dynamic processes in vivo, to accomplish automated image processing, and to identify roles of genes in neuronal biochemical communications.This system will significantly increase the throughput and accuracy of in vivo live imaging experiments in model organisms. It streamlines and automates the painstakingly manual procedure of microscopy, in some cases enables some experiments that are otherwise impossible to do, and reduces the noise and artifacts in these experiments. The image analysis algorithms will provide quantitative data with large throughput to allow good statistics. The approach is innovative because the technologies developed here dramatically increase the capabilities and throughput of current assay tools, enabling key biological experiments that are not currently performed. Furthermore, the technology is broadly applicable to other biological systems and could potentially lead to new therapeutics for related diseases.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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