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kinetics

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kinetics is a package for modelling reactions using ordinary differential equations. It's primarily aimed at modelling enzyme reactions, although can be used for other purposes.

See the Documentation for more information.

kinetics uses scipy.integrate.odeint to solve ordinary differential equations, but extends upon this to allow the use of parameter distributions rather than single parameter values. This allows error to be incorporated into the modelling.

kinetics uses scipy's probability distributions, with a large number of distributions to choose from. Typically uniform, normal, log-uniform or log-normal distributions are used.

Documentation: ReadTheDocs

Github: kinetics

Requirements: NumPy, SciPy, matplotlib, tqdm, pandas, SALib, seaborn, and deap.

Installation: pip install kinetics

Citation: Finnigan, W., Cutlan, R., Snajdrova, R., Adams, J., Littlechild, J. and Harmer, N. (2019), Engineering a seven enzyme biotransformation using mathematical modelling and characterized enzyme parts. ChemCatChem.

Graphical Abstract

Features

  • Construct systems of ODEs simply by selecting suitable rate equations and naming parameters and species
  • Use either simple parameter values or probability distributions
  • Run sensitivity analysis using SALib
  • Easily plot model runs using predefined plotting functions
  • Optimisation using genetic algorithm using DEAP (coming soon)

Release files for kinetics 1.4.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for kinetics 1.4.5
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kinetics-1.4.5.tar.gz 26.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for kinetics 1.4.5
File Interpreter ABI Platform
kinetics-1.4.5-py3-none-any.whl Python 3 none any Details

Total release size: 57.3 kB

Release files / kinetics-1.4.5.tar.gz

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Release files / kinetics-1.4.5-py3-none-any.whl

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