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Nested effects models for high-dimensional phenotyping screens

机译:高维表型筛选的嵌套效应模型

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摘要

Motivation: In high-dimensional phenotyping screens, a large number of cellular features is observed after perturbing genes by knockouts or RNA interference. Comprehensive analysis of perturbation effects is one of the most powerful techniques for attributing functions to genes, but not much work has been done so far to adapt statistical and computational methodology to the specific needs of large-scale and high-dimensional phenotyping screens.
机译:动机:在高维表型筛查中,通过敲除或RNA干扰扰动基因后,观察到大量细胞特征。扰动效应的综合分析是将功能归因于基因的最强大技术之一,但是迄今为止,尚未进行大量工作来使统计和计算方法适应大规模和高维表型筛查的特定需求。

著录项

  • 来源
    《Bioinformatics》 |2007年第13期|i305-i312|共8页
  • 作者单位

    Lewis-Sigler Institute for Integrative Genomics and Department of Computer Science Princeton University Princeton NJ 08544 USA;

    Max Planck Institute for Molecular Genetics Ihnestraße 63-73 14195 Berlin and;

    Institute for Functional Genomics Computational Diagnostics Group University of Regensburg Josef Engertstr. 9 93503 Regensburg Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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