Methods for mining HTS data

被引：38

作者：

Harper, Gavin ^{[1
]}

Pickett, Stephen D. ^{[1
]}

机构：

[1] GSK, Stevenage SG1 2NY, Herts, England

来源：

DRUG DISCOVERY TODAY | 2006年 / 11卷 / 15-16期

关键词：

D O I：

10.1016/j.drudis.2006.06.006

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Data mining is a fast-growing field that is finding application across a wide range of industries. HTS is a crucial part of the drug discovery process at most large pharmaceutical companies. Accurate analysis of HTS data is, therefore, vital to drug discovery. Given the large quantity of data generated during an HTS, and the importance of analyzing those data effectively, it is unsurprising that data-mining techniques are now increasingly applied to HTS data analysis. Taking a broad view of both the HTS process and the data-mining process, we review recent literature that describes the application of data-mining techniques to HTS data.

引用

页码：694 / 699

页数：6

共 56 条

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