  Biochemical computing attempts to process information with biomolecules and
biological objects. In this work we review our results on analysis and
optimization of single biochemical logic gates based on enzymatic reactions,
and a network of three gates, for reduction of the "analog" noise buildup. For
a single gate, optimization is achieved by analyzing the enzymatic reactions
within a framework of kinetic equations. We demonstrate that using
co-substrates with much smaller affinities than the primary substrate, a
negligible increase in the noise output from the logic gate is obtained as
compared to the input noise. A network of enzymatic gates is analyzed by
varying selective inputs and fitting standardized few-parameters response
functions assumed for each gate. This allows probing of the individual gate
quality but primarily yields information on the relative contribution of the
gates to noise amplification. The derived information is then used to modify
experimental single gate and network systems to operate them in a regime of
reduced analog noise amplification.
