Balancing Information and Dissipation with Partially Observed Fluctuating Signals

Biological systems sense and extract information from fluctuating signals while operating under energetic constraints and limited resolution. We introduce a general chemical model in which a signaling pathway is activated by hidden signals and produces a readout molecule. A sensor, here modeled as an abstract optimization agent, is coupled to the signaling process and can tune the readout production. We propose viable strategies for the sensor to estimate, and eventually balance, information gathering on the hidden process and the associated dissipative cost relying solely on counting statistics of observed trajectories. We show that these strategies can be successfully implemented to adapt the readout production even with finite-time measurements and limited dynamic resolution, and remain effective in the presence of inhibitory regulatory mechanisms. Our Letter provides a plausible mechanism to actively balance information and dissipation, paving the way for an implementable design principle underpinning biological and biochemical adaptation.