Molecular computations with competitive neural networks that exploit linear and nonlinear kinetics

We show how to exploit enzymatic saturation -an ubiquitous nonlinear effects in biochemistryin order to process information in molecular networks. The networks rely on the linearity of DNA strand displacement and the nonlinearity of enzymatic replication. We propose a pattern-recognition network that is compact and should be robust to leakage.