Skip to main content

JaxKineticModel

Python package to simulate, build, and train kinetic models.

Installation

git clone https://github.com/AbeelLab/jaxkineticmodel.git
python -m pip install .

Documentation package

Documentation on jaxkineticmodel can be found here

Running experiments as reported in paper

  • Datasets generated from SBML models can be found in datasets
  • Glucose pulse datasets can be found here
  • Experiments as reported in [1] can be found in scripts. Results from these experiments can found in the 4tu-repository

Source code

All data, source code, scripts, and results can be found in the 4tu-repository

Reference

If you use this package in your work, please reference:

[1] Lent, P. V., Bunkova, O., Planken, L., Schmitz, J., & Abeel, T. (2024). Neural Ordinary Differential Equations Inspired Parameterization of Kinetic Models. bioRxiv, 2024-12.

Metadata

Release files for jaxkineticmodel 0.0.4

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

Source distribution (sdist)

Source distribution for jaxkineticmodel 0.0.4
File Size Uploaded
jaxkineticmodel-0.0.4.tar.gz 41.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for jaxkineticmodel 0.0.4
File Interpreter ABI Platform
jaxkineticmodel-0.0.4-py3-none-any.whl Python 3 none any Details

Total release size: 87.7 kB

Release files / jaxkineticmodel-0.0.4.tar.gz

Download URL jaxkineticmodel-0.0.4.tar.gz
Size 41.7 kB
Tags Source
SHA-256 checksum
How to use checksums
a644c0e47113d68471f2639a0ccde128651e6c979fbf6195fe02cd9a861b7e70
BLAKE2b-256 checksum
How to use checksums
dd6e30e6c9c1a06ffc0207821a7ce23416dab851e44d6c17beb7a79900ae9f3c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.18

Release files / jaxkineticmodel-0.0.4-py3-none-any.whl

Download URL jaxkineticmodel-0.0.4-py3-none-any.whl
Size 45.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b08981cc558928d16ae528933a48f764d2c53f60802c0fef8a6421dccb169a5e
BLAKE2b-256 checksum
How to use checksums
755bde460cfe281d28e48f85666d10dd5a0bc8582f30bccd92eb51093a895b16
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.18

Release history Release notifications | RSS feed

This release

0.0.4 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page