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Deciphering circadian clock cell network morphology within the biological master clock, the suprachiasmatic nucleus
Deciphering circadian clock cell network morphology within the biological master clock, the suprachiasmatic nucleus
Abstract: The biological master clock, the suprachiasmatic nucleus (SCN) of a mouse, contains many (~20,000) clock cells heterogeneous, particularly with respect to their circadian period. Despite the inhomogeneity, within an intact SCN, they maintain a very high degree of circadian phase coherence, which is generally rendered visible as system-wide propagating phase waves. The phase coherence …
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Statistical Inference with Neural Network Imputation for Item Nonresponse
Statistical Inference with Neural Network Imputation for Item Nonresponse
Abstract: We consider the problem of nonparametric imputation using neural network models. Neural network models can capture complex nonlinear trends and interaction effects, making it a powerful tool for predicting missing values under minimum assumptions on the missingness mechanism. Statistical inference with neural network imputation, including variance estimation, is challenging because the basis for function …