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Optimizing Kinase Profiling Programs with Deep Learning
Join Genentech and Optibrium for this discussion of Alchemite™, a novel deep learning approach, and its application to optimizing kinase profiling programs. Using Alchemite™ reduces the number of kinase assays required to accurately predict the full kinase selectivity profile, effectively accelerating experimental programs. The team will demonstrate the method’s performance on a data set of approximately 650 kinases and 10,000 compounds, significantly outperforming state-of-the-art quantitative structure-activity relationship (QSAR) approaches, including multi-target deep learning. Furthermore, we will discuss Alchemite’s unique ability to provide reliable prediction-uncertainty-estimates that enable the selection of the most informative kinase assays and which compounds to test.

Jun 2, 2021 11:00 AM in Eastern Time (US and Canada)

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