Skip to main content

Dynamical Modeling of Biological Systems - Quantitative Reactomics

Reason this release was yanked:

Build library incompatibility

Project description

Life123

Open-Source Engine for Quantitative Reactomics.

Dynamical Modeling of Biological Systems in 1, 2 and 3D (as well as single-compartment reactions)

Includes diffusion, reactions, diffusion/reaction, membranes and compartments.

WEBSITE

Fundamental Goals

  1. Detailed, quantitative biological simulations, including whole prokaryotic cells (bacteria), and later eukaryotic cells
  2. Deeper quantitative insight into human tissue/organ/system physiology, for the advancement of medicine
  3. A very integrative approach that is ultimate conducive to body-wide insights, with an eye to Longevity Science
  4. Explore the minimalist essence of life-like dynamical systems
  5. Investigate potential paths for the emergence of life on Earth and on Exoplanets
  6. A community effort bringing together biologists, system biologists, programmers, machine-learning specialists, biochemists, power-computing engineers, doctors, data scientists, graphic designers, members of the public willing to share computing resources, etc.

Overview and Details

WEBSITE

Follow our blog/discussions

Try it Out Live on a hosted JupyterLab!

TRY IT OUT LIVE (no registration nor install!)
Click on Binder

Then explore the notebooks under the experiments folder.

Note that several notebooks create HTML log files, by the same name as the notebook (eg, running the notebook called diffusion_1.ipynb will create a log file named diffusion_1.htm). These log files typically contain additional interactive graphics: currently, mostly interactive diagrams of the reaction networks.
(Most plots will show up inside the notebooks.)

"Binder", the host of the live demo, is akin to Google's Colab: short-term runs on a hosted JupyterLab environment.
It generally takes less than one minute to launch... and then you'll have your own private copy of all the notebooks, to run and/or change and re-run. (The notebooks are pre-existing; you may view them without having to run anything.)

Please remember that nothing gets saved long term on Binder; so, if you make changes you want to preserve, make sure to download the changed notebooks! For instruction on creating your own private local copy, read on...

(Note: if you want to simply VIEW the notebooks rather than run them, you may simply follow the
links in the Experiments Page )

Components

Experiments: See the Life123 List of Experiments

Libraries: See the Life123 Guide

Unit Testing (pytest):

  • "tests" folder (top-level)

How to Use

See this short video

How to Run Locally

pip install life123

For details, see the Life123 Download/Install page

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

life123-1.0rc5.tar.gz (176.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

life123-1.0rc5-py3-none-any.whl (187.4 kB view details)

Uploaded Python 3

File details

Details for the file life123-1.0rc5.tar.gz.

File metadata

  • Download URL: life123-1.0rc5.tar.gz
  • Upload date:
  • Size: 176.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.12

File hashes

Hashes for life123-1.0rc5.tar.gz
Algorithm Hash digest
SHA256 02050fd271e326cf7fc600b03601a97350736d140ccf5eb365b048afa1b14fcd
MD5 15c17cf31f4b2eef93adfa3bed413207
BLAKE2b-256 54277c0c457406b012b20b228f34bb85ba5a6376c1a56429d009f6de57fd5b2d

See more details on using hashes here.

File details

Details for the file life123-1.0rc5-py3-none-any.whl.

File metadata

  • Download URL: life123-1.0rc5-py3-none-any.whl
  • Upload date:
  • Size: 187.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.12

File hashes

Hashes for life123-1.0rc5-py3-none-any.whl
Algorithm Hash digest
SHA256 1c16b7db92eb4848dea04b3e9f9807f0bfc457e8474d257e494ab0178adb9078
MD5 688f0d5a777ffc005190e330dae27ff6
BLAKE2b-256 44465d3d102559ac0123f738ffc10ffdd54d5afcf41543230c1b71f0d49f637f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page