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Network symmetry represents a new vantage point for dissecting complex information processing characteristics in multisite modification, and the breaking of symmetry can confer ordering of modification and absolute concentration robustness.

Single-cell data analysis must be guided by an underlying model.

A multi-compartment spiking neural network model demonstrates that biologically feasible deep learning can be achieved if sensory inputs and higher-order feedback are received by different dendritic compartments.