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Introduction:

Deconvoluting the molecular target signals behind observed drug response phenotypes is an important part of phenotype-based drug discovery and repurposing efforts. We demonstrate here how our network-based deconvolution approach, named target addiction score (TAS), provides insights into the functional importance of druggable protein targets in various cancer cell-based drug response profiling experiments.

Liscence:

The TAS R-package is made available under the terms of the GNU General Public License, which means that the source code is freely available for use within other software, but if you alter the code and distribute it, you must make the new source code freely available as well. This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY. In case you use the package in your work, we do appreciate a citation to the publications below.

Citation:

Bhagwan Yadav, Peddinti Gopalacharyulu, Tea Pemovska, Suleiman A. Khan, Agnieszka Szwajda, Jing Tang, Krister Wennerberg and Tero Aittokallio. From drug response profiling to target addiction scoring in cancer cell models. (Submitted)

Bhagwan Yadav, Tea Pemovska, Agnieszka Szwajda, Evgeny Kulesskiy, Mika Kontro, Riikka Karjalainen, Muntasir Mamun Majumder, Disha Malani, Astrid Murumägi, Jonathan Knowles, Kimmo Porkka, Caroline Heckman, Olli Kallioniemi, Krister Wennerberg, Tero Aittokallio. Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Scientific Reports (2014) 4, 5193; DOI:10.1038/srep05193

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Project Members:

• Bhagwan Yadav (admin)