Rémy Dubois, Arthur Imbert, Aubin Samacoïts, M. Peter, E. Bertrand, Florian Müller, Thomas Walter
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引用次数: 4
Abstract
The localization of messenger RNA (mRNA) molecules inside cells play an important role for the local control of gene expression. However, the localization patterns of many mRNAs remain unknown and poorly understood. Single Molecule Fluorescence in Situ Hybridization (smFISH) allows for the visualization of individual mRNA molecules in cells. This method is now scalable and can be applied in High Content Screening (HCS) mode. Here, we propose a computational workflow based on deep convolutional neural networks trained on simulated data to identify different localization patterns from large-scale smFISH data.
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