Simulating and Optimising Dynamical Models in Python 3
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Updated
Jul 25, 2024 - Python
Simulating and Optimising Dynamical Models in Python 3
A new implementation of a well-known stochastic model for carcinogenesis, augmented with competition dynamics and spatial structuring.
A free, open-source tool for modeling chemical reaction networks in Python
Bayesian inference of stochastic cellular processes with and without memory in Python.
Networkx implementation of the SIS epidemic model for large and heterogeneous networks
Implementation of SIS epidemic model for large and heterogeneous networks
Stochastic Simulator of Chemical Reactions
Numba accelerated implementation of Gillespie's algorithm for simulating stochastic processes
Working with Gillespie algorithm in order to exam Double step gene expression model.
Delay Gillespie Degrade and Fire with variable delay
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