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PySCeS is the Python Simulator of Cellular Systems
PySCeS is the Python Simulator of Cellular Systems. For a network of coupled reactions it does a stoichiometric matrix analysis, calculates the time course and steady state, and does a complete control analysis.
Stochastic simulator for signaling pathways occuring in biological cells. Handles reaction-diffusion processes in 3D tetrahedral meshes.
Please check our new repository: https://github.com/CNS-OIST/STEPS
SFS_CODE (Selection on Finite Sites under COmplex Demographic Events) performs forward population genetic simulations under a general Wright-Fisher model with arbitrary demographic, selective, and mutational effects.
TinkerCell is a software for synthetic biology. The visual interface allows users to design networks using various biological "parts". Models can include modules and multiple cells. Users can program new functions using C or Python. www.tinkercell.
This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...
RANGE: produce random genetic transcription networks in the NEMO language, which when compiled outputs models in Systems Biology Markup Language. Generate synthetic microarray data, or use NEMO alone to SBML-ize a network, or visualize it in cytoscape.
The target system of this project is to develop mathematically efficient program code generator from cellml like biological models described by mathematical markup languages.
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GENESIS (GEneral NEural SImulation System) is a software platform for the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, large networks, and systems-level processes.
Hy3S uses advanced MPI parallelized hybrid stochastic simulation methods to quickly compute the dynamics of biochemical networks with thousands of species/reactions. Many features included (see Home Page). An easy-to-use GUI (Matlab req) is included.
A base for programs. Includes algorythms for Q-learning and SOM's etc. too. Examples: Hamron: Simulates evolution, uses the 2D-renderer. DriveUnit: created for school, for a robotic arm, uses the 3D-renderer. Hlearn: http://www.sagenb.org/home/pub/8
Mitochondiral Infectious Damage Adaptation (MIDA) model of aging
This project provides the source code for the Mitochondiral Infectious Damage Adaptation (MIDA) model of aging.
A probabilistic modeling approach is applied by solving the master equation in mitochondrial quality state space in the presence of fusion-fission events, decay of functional quality, mitophagy and mitochondrial biogenesis, as well as molecular damage originating from a random source or from infectious events during fusion and fission.
The provided source code is written in...
Arena is a computer simulation in which programs compete for CPU time and access to main memory. Processes such as the dynamics of punctuated equilibrium, host-parasite co-evolution and density dependent natural selection are amenable to investigation.
MASyV (Multi-Agent System Visualization) enables one to write agent-based models/cellular automata, eg. in C, visualize them in real time & capture to movie file with MASyVs GUI & message passing lib. Includes examples: Hello World, ants, viral infection
This is a C library with a set of functions that allow the user to evolve biological networks. The user provides a fitness function in C, and the library will do the rest. A few simulation algorithms and examples are included.
The SBML ODE Solver is a command-line tool and programming library (ISO/ANSI C) for construction and numerical integration of an ODE system, derived from an SBML based description of a biochemical reaction network.
Development has moved to https://github.com/raim/SBML_odeSolver . Please download the latest version from there!
SpiNet is a neural simulation tool for large spiking networks with highly heterogeneous synapses. Neurons are modelled as I&F units with dual exponential synaptic conductances. Complex network models can be easily built using the included tool NetBuilder
Fast-DCM (Fast-DynamicCausalModelling) is an open-source addon for the SPM5 toolbox (http://www.fil.ion.ucl.ac.uk/spm/software/spm5/). It accelerates the estimation of Dynamic Causal Models.
runsbml - Pathway Simulation Tool emulates the dynamics of biological pathways by calculating concentrations of biochemical compounds at different times and conditions.