Cells use temporal dynamical patterns to transmit information via signaling pathways. As optimality with respect to the environment is a universal principle in biological URLanisms have evolved optimal ways to transmit information. Here, we use optimal control theory to obtain  optimal dynamical signal patterns that can transmit information efficiently (low power ) and reliably (high accuracy). Adopting an activation-inactivation decoding network, we reproduce several dynamical patterns found in actual signals, such as steep, gradual, and overshooting dynamics. Notably, when minimizing the power of the input signal, the optimal signals exhibit overshooting, which is a biphasic pattern with transient and steady phases; this pattern is prevalent in actual dynamical patterns. We also identify conditions when these three patterns (steep, gradual, and overshooting) confer advantages.
Cells use temporal dynamical patterns to transmit information via signaling pathways. As optimality with respect to the environment plays a fundamental role in biological URLanisms have evolved optimal ways to transmit information. Here, we use optimal control theory to obtain the optimal dynamical signal patterns that can transmit information efficiently (low energy ) and reliably (high accuracy). Adopting an activation-inactivation decoding network, we reproduce several dynamical patterns found in actual signals, such as steep, gradual, and overshooting dynamics. Notably, when minimizing the energy of the input signal, the optimal signals exhibit overshooting, which is a biphasic pattern with transient and steady phases; this pattern is prevalent in actual dynamical patterns. We also identify conditions when these three patterns (steep, gradual, and overshooting) confer advantages.
R
is a universal principle
plays a fundamental role
A
the
R
power
energy
R
power
energy