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Abstract 5323: Integrated computational cell-line modeling of drug sensitivity and high-throughput siRNA screening reveals novel molecular biomarkers for conventional chemotherapy
Conclusions: We present an integrated approach that combines a novel Bayesian multi-task learning model with high-throughput siRNA screens. Our approach aims to uncover sets of important aberrations and allows for the subtyping of drugs based on similarities in targets and mechanisms of action. We integrate our results with high-throughput RNAi experiments to identify synthetic lethal events in specific therapeutic context.
Citation Format: Olga H. Nikolova, Mehmet Gönen, Rodrigo Dienstmann, In Sock Jang, Russell Moser, Silvia Cermelli, Chang Xu, Ryan M. Mitchell, Eduardo Mendez, Carla Grandori, Christopher Kemp, Stephen ...
Source: Cancer Research - September 30, 2014 Category: Cancer & Oncology Authors: Nikolova, O. H., Gonen, M., Dienstmann, R., Jang, I. S., Moser, R., Cermelli, S., Xu, C., Mitchell, R. M., Mendez, E., Grandori, C., Kemp, C., Friend, S., Guinney, J., Margolin, A. Tags: Molecular and Cellular Biology Source Type: research
