Many intracellular signaling pathways are composed of molecular switches, proteins that
transition between two states—on and off. Typically, signaling is initiated when an external …

In a chemical synapse, information flow occurs via the release of neurotransmitters from a
presynaptic neuron that triggers an Action potential (AP) in the postsynaptic neuron. At its …

Stochastic dynamics of several systems can be modeled via piecewise-deterministic time
evolution of the state, interspersed by random discrete events. Within this general class of …

We formulate a mechanistic model capturing the dynamics of neurotransmitter release in a
chemical synapse. The proposed modeling framework captures key aspects such as the …

Cantilever-based nanosensors are increasingly being used as gas and chemical sensors.
We mechanistically model an important source of stochasticity arising in these systems-the …

The canonical approach to modeling stochasticity considers a dynamical system driven by
Gaussian white noise. Here, we propose an alternative hybrid formulation, in which …

This paper investigates the stabilization problem of singularly perturbed hybrid systems with
multi-rate sampling. Firstly, we establish a hybrid model to describe a class of singularly …

Autonomous systems are rapidly making their way into the physical domain, where they
have to interact with human users in unstructured and safety-critical scenarios. The …

Macromolecular complexes have important roles in cellular functions. These complexes are
formed via multi-merization of either a single component (homomers) or multiple …

This paper proposes a methodology to estimate characteristic functions of stochastic
differential equations that are defined over polynomials. For such systems, the time evolution …