Molecular data — global interaction network — drug response

Demo "2D"
Demo "gene X drug"
Demo "survival"

Druggable supports simple user requests regarding correlation of molecular profiles in large scale datasets. This may be helpful in a range of contexts, from evaluating agreement between omics platforms to identifying potential markers of drug response.

The data from major public resources, The Cancer Genome Atlas and The Cancer Cell Line Encyclopedia can be either explored as plots of gene, protein, and drug sensitivity profiles or help in identifying correlates of response to anti-cancer drugs. Furthermore, such correlaions can be traced to clinical treatment profiles in TCGA. An extra feature of Druggable is network context. This is instrumental in both biomarker discovery and evaluation of candidate molecules in the network context.


Refer to this page to get answers to your questions and instructions for some typical tasks.

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Demo "2D"
Demo "gene X drug"
Demo "survival"
Known compatibility issues:
This site best works with Google Chrome (v. 71 or later) and Mozilla Firefox (v. 60 or later). It is also compatible with Edge.
Some functions do not work with IE 11.
The site also works with Apple Safari (v. 12.1, macOS Mojave v10.14.6), other versions of Safari browser can have compatibility issues.
Network-based biomarker discovery and validation:

Marcela Franco, Ashwini Jeggari, Sylvain Peuget, Franziska Böttger, Galina Selivanova, Andrey Alexeyenko Prediction of response to anti-cancer drugs becomes robust via network integration of molecular data Sci Rep 9, 2379 (2019) doi: 10.1186/1471-2105-13-226.

EviNet web resource:

Ashwini Jeggari, Zhanna Alekseenko, José Dias, Johan Ericson, and Andrey Alexeyenko EviNet: a web platform for network enrichment analysis with flexible definition of gene sets Nucleic Acids Res 2018 Jul 2;46(W1):W163-W170. doi: 10.1002/1878-0261.12350.

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Data type Platform ID Scale

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