We model the intrinsic dynamic behavior of a neuron using stochastic differential equations and Brownian motion. Basis of our work is the deterministic one-compartmental multi-con...
We introduce a new approach to model the behavior of neuronal signal transduction networks using stochastic differential equations. We present first a mathematical formulation for...
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
We propose a framework to translate certain subclasses of differential equation systems into distributed protocols that are practical. The synthesized protocols are state machine...