| Abstract | Diffusion mediated signaling is ubiquitous in biology, playing a role in processes as diverse as chemotaxis, quorum sensing, mate seeking, gene regulation, and homeostasis. How much ``information'' can a diffusion based signaling system signal? This talk will describe a framework for posing and answering questions about the information processing performance of a broad class of signal transduction systems. The ingredients include (1) a source of diffusible molecules, (2) a physical medium through which they diffuse, and (3) a ligand-receptor interaction by which the signal is transduced. The source, medium and receptor form a model of a biochemical communications channel. As in classical information theory, the performance of this channel is measured by its capacity, the maximal mutual information between its input and output ensembles. We investigate the capacity of a class of biochemical communications channels through a combination of computer simulations and analytic investigation of limiting cases. The capacity behaves in some respects like that of a classical AWGN (additive white Gaussian noise) channel, although in our case it depends on biochemical parameters such as the diffusion constant and decay rate of ligand molecules, the forward and reverse rate constants for the ligand-receptor binding interaction, and the geometry of the physical medium through which signaling takes place. Contributors to this work include Case Western Reserve graduate students Matthew Garvey, Suparat Chuechote and Edward Agarwala, and CWRU undergraduates Stephen Fleming and Heather McGinnis. Supported by NSF grants DMS-0720142 and DUE-0634612. |
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