There are 10 repositories under biological-simulations topic.
Brian is a free, open source simulator for spiking neural networks.
SimTK OpenSim C++ libraries and command-line applications, and Java/Python wrapping.
:space_invader: JS library for simple biological simulations and cellular automata
A brian2 extension to simulate spiking neural networks on GPUs
A platform for sharing and reusing biomodeling studies including models, simulations, and visualizations of their results
Openfoam library for physiological flow. Solvers and boundary conditions.
Simulating a primordial brain. A biological (spiking) neural network structuring itself through natural selection.
Scripts to create cartoons of 3D genomes
🦐🐟🦈 A framework for simulating millions of interacting Lagrangian particles (or microbes!) in a turbulent ocean.
This repository includes Matlab codes/routines that were used in our manuscript entitled "Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks" that can be found in this preprint: https://arxiv.org/abs/1911.06286
:crystal_ball: Predict DNA assembly clone validity rates - powered by Kappa
Programming with OpenFOAM is explained with a follow-along approach.
3D Spiking neural network simulation exploring Spike Timing Dependent Plasticity (STDP)
Biological evolution simulator
Simulaciones de epidemias 👾 en poblaciones con mezclas homogéneas 👪 utilizando modelos basados en agentes autónomos 🤖
:waxing_gibbous_moon: Pythonic bindings for the Kappa model simulation language
Interactive game to simulate emergence and natural selection in biological systems
An evolution simulation inspired by Biogenesis on Sourceforge.
Automatic pathway assembly with the YeastPathwayKit
Computational Biology Course
A simple mechanics-based approach to simulating cells. Uses a component-based GUI approach
An organism simulation framework based on cell growth and resultant emergent phenomena.
Cemracs 2018 project (CIRM, July-August 2018)
Scripts for analysing MD simulations of nanopores and DNA translocation (ionic current, translocation rate, pore hydrophobicity).
Project for the course of Laboratory Mathematical Modelling held by Professor Marchetti (A.Y. 2023-2024) for the master curse Quantitative and Computational Biology (QCB) at university of Trento, italy.