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EAGER: Synthesizing Signal Processing Functions with Biochemical Reactions

EAGER: Synthesizing Signal Processing Functions with Biochemical Reactions
EAGER:利用生化反应综合信号处理功能
批准号:
0946601
负责人:
Keshab Parhi
金额:
$20.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-08-01 至 2011-07-31

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中文摘要
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英文摘要
This proposal addresses the synthesis of computations and signal processing operations in a novel context: protein-protein biochemistry where the inputs and outputs are quantities of different types of proteins. The project will demonstrate that biochemistry can implement simple and powerful digital signal processing (DSP) operations. Constructs like and decision feedback equalizers will be implemented: given input quantities of proteins, the system performs a decision to deliver a drug or not, adaptively and autonomously. Also band-pass filtering will be implemented: the quantity of output protein is a highly-tuned function of the frequency of the changes in the quantities of input proteins. Other DSP functions such as FFTs will be implemented. The design of such DSP functions will be investigated in an abstract framework, as a proof of concept. (At this time, the research will not attempt to address the experimental application of these ideas in vitro or in vivo). Techniques for analyzing the dynamics of biological systems are well established. However, synthesizing computation with such mechanisms requires new techniques ? and an entirely new mindset. Success in this endeavor will open numerous opportunities in fields such as biochemical sensing and drug delivery. An important goal of the project is to communicate the goals and the impetus for interdisciplinary research to a wide audience. A new graduate-level course will be developed, titled "Circuits, Computation, and Biology" offered jointly through the ECE Department and the new Biomedical Informatics and Computational Biology Program at the University of Minnesota.
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  • 批准号:
    2243053
  • 项目类别:
    Standard Grant
  • 资助金额:
    $32.5万
  • 财政年份:
    2023
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  • 依托单位:
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  • 批准号:
    1954749
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2020
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SHF: Small: Collaborative Research: LDPD-Net: A Framework for Accelerated Architectures for Low-Density Permuted-Diagonal Deep Neural Networks
  • 批准号:
    1814759
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.5万
  • 财政年份:
    2018
  • 负责人:
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  • 依托单位:
EAGER: Low-Energy Architectures for Machine Learning
  • 批准号:
    1749494
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.5万
  • 财政年份:
    2017
  • 负责人:
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  • 依托单位:
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