药物发现
背景(考古学)
计算生物学
利用
生物
数据科学
生物信息学
计算机科学
计算机安全
古生物学
作者
Leland H. Hartwell,Philippe Szankasi,Christopher J. Roberts,Andrew W. Murray,Stephen Friend
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:1997-11-07
卷期号:278 (5340): 1064-1068
被引量:744
标识
DOI:10.1126/science.278.5340.1064
摘要
The discovery of anticancer drugs is now driven by the numerous molecular alterations identified in tumor cells over the past decade. To exploit these alterations, it is necessary to understand how they define a molecular context that allows increased sensitivity to particular compounds. Traditional genetic approaches together with the new wealth of genomic information for both human and model organisms open up strategies by which drugs can be profiled for their ability to selectively kill cells in a molecular context that matches those found in tumors. Similarly, it may be possible to identify and validate new targets for drugs that would selectively kill tumor cells with a particular molecular context. This article outlines some of the ways that yeast genetics can be used to streamline anticancer drug discovery.
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