一种用于高通量筛选中系统误差检测与消除的有效方法。
An efficient method for the detection and elimination of systematic error in high-throughput screening.
作者信息
Makarenkov Vladimir, Zentilli Pablo, Kevorkov Dmytro, Gagarin Andrei, Malo Nathalie, Nadon Robert
机构信息
Department d'informatique, Université du Québec à Montreal, C.P.8888, s. Centre Ville, Montreal, QC, Canada.
出版信息
Bioinformatics. 2007 Jul 1;23(13):1648-57. doi: 10.1093/bioinformatics/btm145. Epub 2007 Apr 26.
MOTIVATION
High-throughput screening (HTS) is an early-stage process in drug discovery which allows thousands of chemical compounds to be tested in a single study. We report a method for correcting HTS data prior to the hit selection process (i.e. selection of active compounds). The proposed correction minimizes the impact of systematic errors which may affect the hit selection in HTS. The introduced method, called a well correction, proceeds by correcting the distribution of measurements within wells of a given HTS assay. We use simulated and experimental data to illustrate the advantages of the new method compared to other widely-used methods of data correction and hit selection in HTS.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
动机
高通量筛选（HTS）是药物发现中的一个早期过程，它允许在一项研究中对数千种化合物进行测试。我们报告了一种在命中选择过程（即活性化合物的选择）之前校正HTS数据的方法。所提出的校正方法可将可能影响HTS中命中选择的系统误差的影响降至最低。所引入的方法称为孔校正，它通过校正给定HTS测定中孔内测量值的分布来进行。我们使用模拟数据和实验数据来说明与HTS中其他广泛使用的数据校正和命中选择方法相比，新方法的优势。
补充信息
补充数据可在《生物信息学》在线获取。
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