Elucidating the mechanism of cellular cougar picture swap

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Genome-wide expression profiling of transcriptional responses to compound treatment for human cell lines is a promising unbiased approach for exploring the modes of action of bioactive compounds.

In recent years, chemically-induced gene expression data have become available via several public databases.

However, the characteristics of cell-specific gene expression profiles and differences in gene expression profiles between cell lines have not been taken into account in these previous studies.

In addition, the previous methods heavily depended on the coverage of drugs in CMap and the availability of gene expression data for diseases, which limit large-scale analyses.

We compared the statistics of the chemically-induced gene expression profile data contained within three different databases: TG-GATEs, CMap, and LINCS. S1 shows a Venn diagram of the numbers of cell lines and compounds included in the three databases.

First, we performed pathway enrichment analyses of regulated genes to reveal active pathways among 163 biological pathways.

However, there are numerous bioactive compounds (including approved drugs) whose mechanisms are unknown.

Drugs interact with target proteins implicated in a disease of interest and are indispensable for maintaining human physiology.

We analyzed control gene expression profiles, measured at 6 (6.4) h, of 68 human cell lines in LINCS by performing hierarchical clustering.

Figure 1a shows the clustering dendrogram of 957 control gene expression profiles, where multiple control profiles under different conditions were prepared for each human cell line. 1b shows the clustering dendrogram of 68 control gene expression profiles, where multiple control gene expression profiles were averaged into a single profile for each of 68 human cell lines.

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