Information transmission in a two-step cascade: Interplay of activation and repression
arXiv:2109.12901
Abstract
We present an information-theoretic formalism to study signal transduction in four architectural variants of a model two-step cascade with increasing input population. Our results categorize these four types into two classes depending upon the effect played out by activation and repression on mutual information, net synergy, and signal-to-noise ratio. Within the Gaussian framework and using the linear noise approximation, we derive the analytic expressions for these metrics to establish their underlying relationships in terms of the biochemical parameters. We also verify our approximations through stochastic simulations.
arXiv comment10 pages, 4 figures
References in corpus (12)
- Information flow and optimization in transcriptional control
- Nonnegative Decomposition of Multivariate Information
- Exploration of synergistic and redundant information sharing in static and dynamical Gaussian systems
- Signal detection, modularity and the correlation between extrinsic and intrinsic noise in biochemical networks
- Optimal signal processing in small stochastic biochemical networks
- The role of input noise in transcriptional regulation
- The effect of feedback on the fidelity of information transmission of time-varying signals
- Extending the linear-noise approximation to biochemical systems influenced by intrinsic noise and slow lognormally distributed extrinsic noise
- Redundancy in the information transmission in a two-step cascade
- Role of relaxation time scale in noisy signal transduction
- Lecture notes on stochastic models in systems biology
- Information processing in a simple one-step cascade