Skip to main content

Python framework for building and analysing protein allocation models

Project description

PAModelpy - Protein Allocation Model reconstruction in Python

What is PAModelpy?

Models of metabolism are powerful tools to explore the metabolic potential of microorganism. Powerful tools have been created to support Python-based analysis of genome-scale models. These models, however, cannot capture all metabolic phenotypes and the simulation results have high flux variability. Adding protein to each reaction increases the simulation fidelity. The PAModelpy package is designed to integrate protein constraints and protein sectors as described by Alter et al. (2021) to metabolic models. It is the Python implementation of the PAM MATLAB framework to create GECKO like ME models.

The PAModelpy package builds upon the community-wide used COBRApy. We have extended this package with the following features:

  • protein-reaction associations
  • infrastructure to include isozymes and promiscuous enzymes
  • protein sectors
  • specialized objects to build protein allocation models
  • the possibility to perform a computational efficient sensitivity analysis

Installation

PAModelpy is a PiPy package which allows for easy installation with pip:

pip install PAModelpy

Note that the package has been tested with the Gurobi solver.

Code structure:

  • EnzymeSectors: The objects which are used to store the data of the different enzyme sectors which are added to the genome-scale model
  • PAModel: Proteome Allocation (PA) model class. This class builds on to the cobra.core.Model class from the COBRApy toolbox with functions to build enzyme sectors, to add enzyme kinetics parameters and in the future to perform a sensitivity analysis on the enzyme variables.
  • Enzyme: Different classes which relate enzymes to the model with enzyme constraints and variables.
  • CatalyticEvent: A class which serves as an interface between reactions and enzyme. This allows for easy lookup of Protein-Reaction assocations.
  • PAMValidator: Functions to validate the model predictions with physiology data and giving a graphical overview. The script uses data for E.coli (found in ./Data/Ecoli_physiology) by default.

Dependencies

The dependencies of the PAModelpy package can be found in src/pyproject.toml

License

Copyright institute of Applied Microbiology, RWTH Aachen University, Aachen, Germany (2023)

PAModelpy is free of charge open source software, which can be used and modified for your particular purpose under the MIT or Apache 2.0 of the users choice.

Please note that according to these licenses, the software is provided 'as is', WITHOUT WARRANTY OF ANY KIND, without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

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

PAModelpy-0.0.3.8.tar.gz (36.2 kB view details)

Uploaded Source

Built Distribution

PAModelpy-0.0.3.8-py3-none-any.whl (40.2 kB view details)

Uploaded Python 3

File details

Details for the file PAModelpy-0.0.3.8.tar.gz.

File metadata

  • Download URL: PAModelpy-0.0.3.8.tar.gz
  • Upload date:
  • Size: 36.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for PAModelpy-0.0.3.8.tar.gz
Algorithm Hash digest
SHA256 dc2afe9d3e8ac155f9504d381aa1dff991923ffb13ffd079d99ea54e6734947e
MD5 2758919d7669980695373f8a925750b2
BLAKE2b-256 ba0f23518a3c458c1be875fe1b17cd5c7747ac5100c58146e5387a77f0cdce7a

See more details on using hashes here.

File details

Details for the file PAModelpy-0.0.3.8-py3-none-any.whl.

File metadata

  • Download URL: PAModelpy-0.0.3.8-py3-none-any.whl
  • Upload date:
  • Size: 40.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for PAModelpy-0.0.3.8-py3-none-any.whl
Algorithm Hash digest
SHA256 a860fda3731973dee7b070c9d737bfa3459952599309781b3e1aed06977cb7ec
MD5 a39b608c3831fbdfbc97854b57cb45ee
BLAKE2b-256 ae227db21061c2100f69672b59c21b5469b314430aa03ae132cf26cb9874c648

See more details on using hashes here.

Supported by

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