Martina Prugger

The paper introduces tools for parameter estimation of biochemical networks using stability constraints, validated on MTOR network data from breast cancer cells.

This paper introduces a dynamical low-rank method to solve the chemical master equation for biological reaction networks, enabling efficient simulation of large systems.

This paper introduces an unsupervised logic-based method to infer mechanistic hypotheses of cellular processes from state transitions, recovering dynamics and biochemical species concentration changes.

The paper presents GPU-SSA, a GPU-accelerated implementation of the Stochastic Simulation Algorithm, showing significant speedup over CPU implementations for chemical reaction simulations.