BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Christoph Zechner (SISSA) DTSTART:20261112T130000Z DTEND:20261112T150000Z DTSTAMP:20261026T125256Z UID:PSMQFT/15 DESCRIPTION:Title: Quantifying information transfer in biochemical networks\nby Christoph Zechner (SISSA) as part of Probability\, Statistical Mechanics and Quantu m Fields\n\nLecture held in 134.\n\nAbstract\nLiving cells possess remarka ble information processing capabilities\, ranging from cell-fate determina tion to chemotaxis. These capabilities arise from biochemical reaction net works\, whose stochastic dynamics can be described mathematically using co unting processes. Quantifying information transfer in such systems\, howev er\, poses both computational and conceptual challenges. Exact information rates are difficult to obtain even for simple networks\, motivating Gauss ian small-noise approximations that are expected to become accurate at lar ge molecular copy numbers. Yet these approximations can yield qualitativel y incorrect information rates even in this regime. In this talk\, I will d iscuss how this discrepancy arises from the distinction between reaction- and concentration-based descriptions of biochemical trajectories. Conventi onal Gaussian descriptions combine the contributions of distinct reaction channels into effective concentration fluctuations\, thereby discarding in formation carried by individual reaction events. I will use Duncan’s the orem to derive reaction-based Gaussian information rates that agree with t hose of the discrete counting-process model in the large-volume limit. I w ill then connect this time-domain formulation to the Fourier-space approac h\, which allows these rates to be calculated conveniently from the spectr al densities of the input and output signals. Finally\, I will discuss the conceptual and biological implications of this distinction: under what co nditions can downstream biochemical networks access information carried by individual reaction events? I will show how active reaction cycles can ma ke this information accessible through molecular concentrations and connec t these results to the limits of cellular sensing.\n LOCATION:https://researchseminars.org/talk/PSMQFT/15/ END:VEVENT END:VCALENDAR