Abstract: The stochastic effects in photoresist patterning is of great concern in the implementation of EUV lithography. The stochastic nature of EUV chemically amplified resist requires new modeling ...

Cellular dynamics are intrinsically noisy, so mechanistic models must incorporate stochasticity if they are to adequately model experimental observations. As well as intrinsic stochasticity in gene ...

GillespieSSA2 is a fast, scalable, and versatile framework for simulating large systems with Gillespie’s Stochastic Simulation Algorithm (SSA) (Cannoodt et al. 2021). This package is the spiritual ...

The Gillespie algorithm provides statistically exact methods for simulating stochastic dynamics modeled as interacting sequences of discrete events including systems of biochemical reactions or ...

This important study introduces a fully differentiable variant of the Gillespie algorithm as an approximate stochastic simulation scheme for complex chemical reaction networks, allowing kinetic ...

Abstract: This paper targets the acceleration of complex stochastic simulations of biochemical systems by a dedicated hardware architecture on configurable devices (FPGA). Existing approaches are ...

The mechanistic understanding of why neuronal population activity hovers on criticality remains unresolved despite the availability of experimental results. Without a coherent mathematical framework, ...

ABSTRACT: Biochemical systems have numerous practical applications, in particular to the study of critical intracellular processes. Frequently, biochemical kinetic models depict cellular processes as ...

Stochastic modeling techniques have emerged as a powerful tool to study the time evolution of processes in many research fields including (bio)chemical engineering and biology. One of the most applied ...