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High-throughput single-cell-resolution genetic and pharmacological screens using

High-throughput single-cell-resolution genetic and pharmacological screens using
高通量单细胞分辨率遗传和药理学筛选
批准号:
8144996
负责人:
Mehmet Fatih Yanik
金额:
$40.0万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-01 至 2011-03-31

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中文摘要
翻译
尽管花费数十亿美元用于开发靶向中枢神经系统(CNS)的新药,但仍然没有针对许多破坏性神经障碍、疾病、中风和创伤的疗法。现有的高通量筛选技术的局限性已经显著阻碍了CNS药物的发现。中枢神经系统具有独特的和戏剧性的复杂性,需要一个新的模式,在药物筛选。我们提出了一种高通量筛选技术,该技术将允许最复杂的单细胞分辨率遗传和药理学筛选,其通过使用组合蛋白质模式以亚微米分辨率和大规模地指导轴突发生和突触发生。
英文摘要
Despite the expenditure of billions of dollars on the development of new pharmaceuticals targeting the central nervous system (CNS), there are still no therapies against many devastating neurological disorders, diseases, stroke, and trauma. Limitations of existing high-throughput screening technologies have significantly hindered discovery of pharmaceuticals for the CNS. The CNS possesses a unique and dramatic complexity that requires a new paradigm in pharmaceutical screening. We propose a high- throughput screening technology that will permit most sophisticated single-cell resolution genetic and pharmacological screens by directing neuritogenesis and synaptogenesis at sub-micron resolution and on a large scale using combinatorial protein patterns.
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会议论文
Generating transplantable neurons by in vivo combinatorial screening of transcrip
Generating transplantable neurons by in vivo combinatorial screening of transcrip
Generating transplantable neurons by in vivo combinatorial screening of transcrip
Generating transplantable neurons by in vivo combinatorial screening of transcrip
国内基金
海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: