Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.

Reaction Network is a Python package for predicting likely inorganic chemical reaction pathways using graph theoretical methods. Project led by @mattmcdermott (formerly at Berkeley Lab).

A Julia package that implements a category of reaction (transportation) network-type dynamical systems.

Gillespie Stochastic Simulation Algorithm

An interface between the Materials Project software suite and the Schrodinger Python API, designed to allow for high-throughput execution of Jaguar and AutoTS calculations for molecular thermodynamics and kinetics.

A python implementation of open-source packages to explore the chemical reaction space associated with elementary prebiotic chemistry.

Open Markov Proceses as TensorFlow objects, Petri Nets and Chemical Rxn Nets in Haskell

The precomplex generator is a tool for obtaining suitable input structures for automated transition-state (TS) searches (precomplexes) based on single-ended reaction path optimization algorithms.

Automated chemical reaction networking with long-timescale kinetic simulations in Julia

Various ODEs

A Python package for representing reaction networks and simulating their behaviors

Modeling signaling networks in cancer

MASSpy mathematical simulation program via BioSimulators-compliant command-line interface and Docker container

The biological network mining workflow identifies frequent structural patterns in biochemical reaction networks encoded in the Systems Biology Markup Language (SBML)

A package for researchers working with biological oscillations

Code used in arXiv:1808.08630

Dynamic Boltzmann Machine for Lattice Chemical Kinetics

Code used in paper "Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions" arXiv 1905.12122

This is a program to query and extract all the species info, inside KIDA database.

This repository contains the source code of the paper "State and parameter estimation from exact partial state observation in stochastic reaction networks" by Muruhan Rahinam and Mingkai Yu.