Homologous chromosomes undergo sequential quasi-stable interactions during meiotic prophase

Assaf Zaritsky
Deep learning has emerged as the technique of choice for identifying hidden patterns in cell imaging data, but is often criticized as ‘black-box’. Here, we demonstrate that a generative neural network captures subtle details of cell appearance, which permit the prediction of the metastatic efficiency of patient-derived melanoma xenografts with known clinical outcomes. To probe the predictor, we used the network to generate “in-silico” cell images that amplified the critical predictive cellular features. These images...
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