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Deep Learning-Based Subcellular Phenotyping of Cell Edge Dynamics Reveals Fine-Grained Drug Responses
Kwonmoo Lee, Worcester Polytechnic Institute
We'll highlight how unsupervised deep learning can reveal subcellular drug responses hidden in the heterogeneity in live cell images. We'll present a feature-learning method for time-series data, which combines long short-term memory autoencoder and the prior information from traditional machine-learning analysis. We'll discuss how feature learning can be used to identify drug-related rare phenotypes and accelerate drug discovery. You need to have basic knowledge about autoencoder, clustering, microscopy, and cell biology.