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Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

  • PLoS Computational Biology, 13(2), 1-25, 2017

Publisher: Public Library of Science


Signaling pathways play a key role in complex diseases such as cancer, for which the development of novel therapies is a difficult, expensive and laborious task. Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process. In particular, network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics. However, their use is currently hampered by limitations in our knowledge of the underlying biochemistry, as well as in the experimental and compu ...

CEB Authors



ISI Web of Science® Citations: 4


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