The Use of Rate Distortion Theory to Evaluate Biological Signaling Pathways
Cells must make decisions based on noisy measurements of their environment. One way for cells to manage this noise is to attempt to minimize its effect. However, this may not always be possible, or may prove to be costly. On the other hand, the noise may be managed so that the correct decision is made most of the time. Shannon introduced rate distortion theory to evaluate the efficiency of systems like this in which error free communication may not be possible or needed. Here, we show how rate distortion theory can be used to analyze cellular decision processes. We show how several stimulus-response curves that are frequently observed in biological signaling pathways arise naturally as the optimal decision strategy based on rate distortion theory.
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