MatchMaker: A Deep Learning Framework for Drug Synergy Prediction

Drug combination therapies have been a viable strategy for the treatment of complex diseases such as cancer due to increased efficacy and reduced side effects. However, experimentally validating all possible combinations for synergistic interaction even with high-throughout screens is intractable du...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics 2022-07, Vol.19 (4), p.2334-2344
Hauptverfasser:	Kuru, Halil Ibrahim, Tastan, Oznur, Cicek, A. Ercument
Format:	Artikel
Sprache:	eng
Schlagworte:	cancer cell lines chemical features Chemicals Combinatorial analysis Computer applications Computer architecture Deep learning drug synergy Drugs Gene expression Microprocessors Prediction algorithms Predictive models Side effects
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