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dc.contributor.authorNiederdorfer, Barbara
dc.contributor.authorTouré, Vasundra
dc.contributor.authorVazques, Miguel
dc.contributor.authorThommesen, Liv
dc.contributor.authorKuiper, Martin Tremen R.
dc.contributor.authorLægreid, Astrid
dc.contributor.authorFlobak, Åsmund
dc.description.abstractDiscrete dynamical modeling shows promise in prioritizing drug combinations for screening efforts by reducing the experimental workload inherent to the vast numbers of possible drug combinations. We have investigated approaches to predict combination responses across different cancer cell lines using logic models generated from one generic prior-knowledge network representing 144 nodes covering major cancer signaling pathways. Cell-line specific models were configured to agree with baseline activity data from each unperturbed cell line. Testing against experimental data demonstrated a high number of true positive and true negative predictions, including also cell-specific responses. We demonstrate the possible enhancement of predictive capability of models by curation of literature knowledge further detailing subtle biologically founded signaling mechanisms in the model topology. In silico model analysis pinpointed a subset of network nodes highly influencing model predictions. Our results indicate that the performance of logic models can be improved by focusing on high-influence node protein activity data for model configuration and that these nodes accommodate high information flow in the regulatory network.en_US
dc.publisherFrontiers Mediaen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleStrategies to Enhance Logic Modeling-Based Cell Line-Specific Drug Synergy Predictionen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.source.journalFrontiers in Physiologyen_US
dc.description.localcodeCopyright © 2020 Niederdorfer, Touré, Vazquez, Thommesen, Kuiper, Lægreid and Flobak. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal