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Fig. 1 | Genome Biology

Fig. 1

From: DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data

Fig. 1

(Sub) Neural network architecture of DeepImpute. Each sub-neural network is composed of four layers. The input layer is genes that are highly correlated with the target genes in the output layer. It is followed by a dense hidden layer of 256 neurons dense layer and a dropout layer (dropout rate = 20%). The output layer consists of a subset of target genes (default N = 512), whose zero values are to be imputed

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