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Incoherent feedforward networks exhibit the ability to generate temporal pulse behavior. However, exerting control over specific dynamic properties, such as amplitude and rise time, poses a challenge and is intricately tied to the network’s implementation. In this study, we focus on analyzing sequestration-based networks capable of exhibiting pulse behavior. By employing time-scale separation in the fast sequestration regime, we approximate the temporal dynamics of these networks. This approach allows us to establish a mapping that elucidates the impact of varying the kinetic rates and pulse specifications, including amplitude and rise time. Furthermore, we introduce a positive feedback mechanism to regulate the amplitude of the pulsing response.more » « lessFree, publicly-accessible full text available December 16, 2025
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Cellular signaling pathways are responsible for decision making that sustains life. Most signaling pathways include post-translational modification cycles, that process multiple inputs and are tightly interconnected. Here we consider a model for phosphorylation/dephosphorylation cycles, and we show that under some assumptions they can operate as molecular neurons or perceptrons, that generate sigmoidal-like activation functions by processing sums of inputs with positive and negative weights. We carry out a steady-state and structural stability analysis for single molecular perceptrons as well as for feedforward interconnections, concluding that interconnected phosphorylation/dephosphorylation cycles may work as multilayer biomolecular neural networks (BNNs) with the capacity to perform a variety of computations. As an application, we design signaling networks that behave as linear and non-linear classifiers.more » « less
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