We present a stochastic framework to study signal transmission in a generic two-step cascade S \rightarrow X \rightarrow Y. Starting from a set of Langevin equations obeying Gaussian noise processes we calculate the variance and covariance associated with the system components . These quantities are then used to calculate the net synergy within the purview of partial information decomposition. We show that redundancy in information transmission is essentially an important consequence of Markovian property of the two-step cascade motif  .
We present a stochastic framework to study signal transmission in a generic two-step cascade S \rightarrow X \rightarrow Y. Starting from a set of Langevin equations obeying Gaussian noise processes we calculate the variance and covariance while considering both linear and nonlinear production terms for different biochemical species of the cascade . These quantities are then used to calculate the net synergy within the purview of partial information decomposition. We show that redundancy in information transmission is essentially an important consequence of Markovian property of the two-step cascade motif . We also show that redundancy increases fidelity of the signalling pathway .
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associated with the system components
while considering both linear and nonlinear production terms for different biochemical species of the cascade
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. We also show that redundancy increases fidelity of the signalling pathway