Living systems gather and transmit information about the internal and external environments through biochemical networks of interacting molecules. The robustness and fidelity of information processing in biochemical networks can be limited by noise, the structure of biochemical interactions or numbers of participating molecules. Living cells, as a whole, are highly dissipative and it has been long recognized that information processing too require consumption of energy. Less is known about the limits and energetic cost imposes on the capacity of information processing through biologically relevant biochemical reaction networks. Combining non-equilibrium statistical physics and learning theory perspectives we derive fundamental constraints relating the amount of dissipated energy and the fidelity and speed of information processing in individual cell signaling modules. We derive the limits on equilibrium modules imposed by the available complexity and cooperativity but also by the range of input signals. Finally we analyze the information processing requirements to the energy budget of the cell.
