Capacity of a Simple Intercellular Signal Transduction Channel

TL;DR

This paper models biochemical signal transduction as a finite-state Markov channel called the BIND channel, deriving its capacity, showing the optimal input distribution, and comparing it to Poisson channels.

Contribution

It introduces the BIND channel model for biochemical signaling, derives its capacity, and analyzes the effects of feedback and limits, providing new insights into cellular communication.

Findings

Capacity is achieved with IID input distribution.

Feedback does not increase channel capacity.

Channel capacity approaches that of Poisson channels in certain limits.

Abstract

We model biochemical signal transduction, based on a ligand-receptor binding mechanism, as a discrete-time finite-state Markov channel, which we call the BIND channel. We show how to obtain the capacity of this channel, for the case of binary output, binary channel state, and arbitrary finite input alphabets. We show that the capacity-achieving input distribution is IID. Further, we show that feedback does not increase the capacity of this channel. We show how the capacity of the discrete-time channel approaches the capacity of Kabanov's Poisson channel, in the limit of short time steps and rapid ligand release.