Generate realizations of stochastic processes in python.
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Updated
Dec 9, 2022 - Python
Generate realizations of stochastic processes in python.
BioSCRAPE (Bio-circuit Stochastic Single-cell Reaction Analysis and Parameter Estimation)
ANTARES Visualizations
StochPy is a versatile stochastic modeling package which is designed for stochastic simulation of molecular control networks
DelaySSAToolkit.jl: a tool in Julia for stochastic simulation with delays
Networkx implementation of the SIS epidemic model for large and heterogeneous networks
Multiscale Modelling Tool - mathematical modelling without the maths
🦜 DISCOTRESS 🦜 is a software package to simulate and analyse the dynamics on arbitrary Markov chains
Implementation of SIS epidemic model for large and heterogeneous networks
Fractional calculus and commercial air transport models used in: arxiv.org/abs/1601.07655
Python code of the Decadal and Hierarchical Markov Chain (DHMC) model for stochastic simulation of daily rainfall
FERN (Framework for Evaluation of Reaction Networks) is an extensible and comprehensive framework for efficient simulations and analysis of chemical reaction networks written in Java.
Fast R implementation of Gillespie's Stochastic Simulation Algorithm
BioNetGen biochemical network simulation program via BioSimulators-compliant command-line interface and Docker container
Implementation of SIS epidemic model for large and heterogeneous networks using Fortran.
nSBM: multi branch topic modeling
Usefull models simulating stochastic processes in different times scales with or without reproduction of long-term percistence (Hurst-Kolmogorov behaviour). Also a simple tool for determening the Hurst coefficient is provided. All code is in the form of Matlab functions.
Implementation of SIS epidemic model with a Gillespie Algorithm - NOT optimized
STOCBIONET is a software for stochastic simulation of biochemical networks
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