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用CMAP来辅助你做药物研究-探索药物,表达,表型的关系

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发表于 2017-3-5 00:00:55 | 显示全部楼层 |阅读模式
这个非常重要,一直想写的,其实我以前给很多生信菜鸟团小伙伴都安利过,今天又看到了,先放在这里哈!



One approach that has been used widely in cancer drug discovery is Connectivity Mapping [5].

The Connectivity Map (also known as “CMAP”) is a collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive small molecules analyzed using pattern-matching algorithms that discover relationships between the drugs, gene expression changes, and the phenotypes.

This computational approach has greatly facilitated drug screening studies, as CMAP contains more than 7000 gene expression profiles for approximately 1300 compounds (https://www.broadinstitute.org/cmap/). In particular, it has been employed in many studies for discovering repurposing drugs against common diseases, including diabetes and Alzheimer’s disease [5], and for treating solid tumors, including those associated with colon cancer [6], breast cancer [7], and lung adenocarcinoma [8].

The basic approach for CMAP-based drug discovery studies is the identification of disease- (or phenotype) associated genomic signatures that inversely correlate with perturbation in the genomic signature associated with the administration of molecules or drugs [5].
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 楼主| 发表于 2017-3-5 11:36:29 | 显示全部楼层
有看到一篇:http://journals.plos.org/plosone ... ournal.pone.0150460
The latest version of CMAP consists of gene expression profiles of five cell lines treated with ~1,300 compounds, from which many in silico DR methods were developed using this dataset either alone or in combination with other information
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