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Data Denoising using AI for improving the accuracy of Solid-State Nanopore Sensing

Data Denoising using AI for improving the accuracy of Solid-State Nanopore Sensing
使用 AI 进行数据去噪以提高固态纳米孔传感的准确性
批准号:
CCARD-2022-00591
负责人:
Renaud, Eric
金额:
$2.38万
依托单位:
依托单位国家:
加拿大
项目类别:
CCI Applied Research and Development Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
北方纳米孔仪器公司(NNI)是从2020年成立的渥太华大学剥离出来的一家仪器公司,专门从事研究工具和解决方案,以支持固态纳米孔的基础和应用研究。渥太华La Cité的智能原型专业技术中心(CEPI)将对该项目进行应用研究,该中心拥有人工智能方面的专业知识。固态纳米孔--薄膜上大小与DNA分子或典型蛋白质相似的小孔--将颠覆多个关键市场,包括蛋白质组学、DNA测序、药物发现、下一代数字信息存储等。其工作原理很简单:当在导电溶液中通过纳米孔施加电压时,离子电流被驱动通过孔,生物分子将在通过过程中阻止离子流。如果仔细解码这种阻塞信号的形状和特征,就可以提供有关转运分子的丰富信息。NNI的产品之一是名为Nanolyzer的分析和信号处理套件,旨在分析和解释纳米孔操作过程中产生的信号。通常,从纳米孔传感收集的信号会受到来自多个来源的噪声的污染。传统的基于频率的滤波会使信号失真,并使分析进一步复杂化。这个项目的目标是使用深度学习方法将信号从噪声中分离出来,从而以最小的信号失真减少噪声。这个值将是一个更好的信号信噪比,改善了对生物分子通过纳米孔产生的信号的解释。CEPI的团队将帮助北方纳米孔仪器实现这一目标。
英文摘要
Northern Nanopore Instruments (NNi), a spin-off of the University of Ottawa incorporated in 2020, is an instrumentation company that specializes in research tools and solutions to support fundamental and applied research on solid-state nanopores. The Center of Expertise in Smart Prototyping (CEPI) of La Cité in Ottawa which will do the applied research on this project has expertise in AI. Solid-state nanopores-tiny holes in thin membranes similar in size to a molecule of DNA or a typical protein-are set to disruptive multiple critical markets, including proteomics, DNA sequencing, drug discovery, next-generation digital information storage, and more. The operating principle is simple: when a voltage is applied across the nanopore in conductive solution, ionic current is driven through the pore, and biomolecules will block the ionic current during passage. The shape and characteristic of that blockage signal, if carefully decoded, provides a wealth of information about the translocating molecule. One of NNi's product offerings in an analysis and signal processing suite called Nanolyzer, intended to analyze and interpret the signals generated during nanopore operation. Typically, signals collected from nanopore sensing are polluted with noise from numerous sources. Traditional frequency-based filtering distorts the signal and further complicates analysis. This project goal is to use a deep learning approach to separate signal from noise and thereby reduce the noise with minimal distortion to the signal. The value would be a better signal signal-to-noise ratio improving interpretation of the signals generated by biomolecules passing through the nanopore. The CEPI's team will help Northern Nanopore Instruments achieve this goal.
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Integration of semi-conductors manufacturing physics equation into an artificial intelligence model to improve predictions and detect anomalies
  • 批准号:
    CCARD-2022-00259
  • 项目类别:
    CCI Applied Research and Development Grants
  • 资助金额:
    $2.19万
  • 财政年份:
    2022
  • 负责人:
    Renaud, Eric
  • 依托单位:
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