Mining chemical structural information from the drug literature

被引：44

作者：

Banville, DL ^{[1
]}

机构：

[1] AstraZeneca, Wilmington, DE 19850 USA

来源：

DRUG DISCOVERY TODAY | 2006年 / 11卷 / 1-2期

关键词：

D O I：

10.1016/S1359-6446(05)03682-2

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

It is easier to find too many documents on a life science topic than to find the right information inside these documents. With the application of text data mining to biological documents, it is no surprise that researchers are starting to look at applications that mine out chemical information. The mining of chemical entities - names and structures - brings with it some unique challenges, which commercial and academic efforts are beginning to address. Ultimately, life science text data mining applications need to focus on the marriage of biological and chemical information.

引用

页码：35 / 42

页数：8

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