Modeling light inducible protein interaction systems via ODEs.

Evaluating numerical methods for approximating ODE using Python

Tools for numerical analysis of ODE in python

Soft Magnetic Materials and Ordinary Differential Equations: From Linear Circuits to Neural Network Models

Putting [A]NODEs ([Augmented] Neural ODEs) to work, for Time Series prediction and simulation

Stochastic Simulator of Chemical Reactions

This project uses Python to simulate single pendulum and double pendulum. Simultaneously we explore the influence of different parameters on the motion of the system.

Learning about optimizing objective functions, efficient modeling and simulation algorithms in computational science.

COVID-19 modeling with ODEs and Markov chains. Validation results are provided, including analysis of the outbreak under the so called 'dynamic clearing' strategy.

Part of MSc Biology Project (2/2). Ordinary Differential Equations (ODE) model for modelling protein, more specifically Sfp1, translocation.

A 3d engine which can plot graphs, curves, ode solutions and vector fields

A complete end-to-end pipeline for single-molecule FRET trajectory processing, 3-state kinetic modeling with bleaching, global ensemble fitting, bootstrapping, and sensitivity analysis for Hsp90 dynamics.

Context-dependent pharmacology of cannabidiol: A two-pathway model linking mitochondrial VDAC gating and bioenergetic resilience to selective cytotoxicity

BADDADAN is a proof of concept which builds ODE models of gene modules to study the response of A. thaliana to stress

This repository contains a simulation of a pendulum-powered cart. The simulation models the dynamics of a cart that is powered by the swinging of a pendulum attached to it. The motion of the cart is determined by the motion of the pendulum, which is affected by the force applied to the cart and the pendulum's initial conditions.

Complements mitoSim - the simulator of cell mitochondria as a spacelss graph.

Simulator for SAIR model proposed in Piqueira, J. R. C., Navarro, B. F., & Monteiro, L. H. A. (2005). Epidemiological models applied to viruses in computer networks. Journal of Computer and System Sciences.

An interactive web application for exploring cell cycle models

This repository contains a robust and flexible Python package for solving ordinary differential equations (ODEs). It supports both Runge–Kutta schemes (explicit, DIRK) and BDF multistep methods, with adaptive time-stepping and strong support for sparse Jacobians--making it well-suited for large-scale and stiff problems.

Blender add-on to generate strange attractors.