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Title: Drug target optimization in chronic myeloid leukemia using innovative computational platform.
Authors: Chuang, Ryan
Hall, Benjamin A.
Benque, David
Cook, Byron
Ishtiaq, Samin
Piterman, Nir
Taylor, Alex
Vardi, Moshe
Koschmieder, Steffen
Gottgens, Berthold
Fisher, Jasmin
First Published: 3-Feb-2015
Publisher: Nature Publishing Group
Citation: Scientific Reports, 2015, 5 : 8190
Abstract: Chronic Myeloid Leukemia (CML) represents a paradigm for the wider cancer field. Despite the fact that tyrosine kinase inhibitors have established targeted molecular therapy in CML, patients often face the risk of developing drug resistance, caused by mutations and/or activation of alternative cellular pathways. To optimize drug development, one needs to systematically test all possible combinations of drug targets within the genetic network that regulates the disease. The BioModelAnalyzer (BMA) is a user-friendly computational tool that allows us to do exactly that. We used BMA to build a CML network-model composed of 54 nodes linked by 104 interactions that encapsulates experimental data collected from 160 publications. While previous studies were limited by their focus on a single pathway or cellular process, our executable model allowed us to probe dynamic interactions between multiple pathways and cellular outcomes, suggest new combinatorial therapeutic targets, and highlight previously unexplored sensitivities to Interleukin-3.
DOI Link: 10.1038/srep08190
eISSN: 2045-2322
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2015. This is an open-access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Computer Science

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