DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
Johannes Kepler University of Linz · University of Cambridge · +1 more institution
Abstract
Motivation: While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a time- and cost-efficient way to prioritize combinations to test, based on recently available large-scale combination screening data. Recently, Deep Learning has had an impact in many research areas by achieving new state-of-the-art model performance. However, Deep Learning has not yet been applied to drug synergy prediction, which is the approach we present here, termed DeepSynergy. DeepSynergy uses chemical and genomic information as input information, a…
Citation impact
- FWCI
- 27.74
- Percentile
- 100%
- References
- 76
Authors
6Topics & keywords
- Random forest
- Gradient boosting
- Machine learning
- Normalization (sociology)
- Artificial intelligence
- Computer science
- Boosting (machine learning)
- Support vector machine
- Good health and well-being