symbolic-compartmental-model 0.1.1

Analyzing protein-complex dynamics using metabolic age quantified by stable-isotope labeling

symbolic-compartmental-model

A symbolic package based on SymPy for simulating and fitting Compartmental Models (CMs).

Overview

Symbolic Compartmental Model is a python package for constructing, simulating, and fitting compartmental models. It is based on the symbolic calculations package sympy but can also perform numerical calculations.

Current Features

• Defining a CM based on the contributed turnovers (M-matrix) and observed pool sizes
• Optionally include symbolic parameters and set their bounds for later fitting
• Several fitting functions, including single/multiple pools and mass balance constraints (optional)
• Both numerical and symbolic outputs for dynamic parameters: age, residence time, decay rate, etc.
• Plotting of simulated data

Getting started

• For installing the package in your current python environment, can simply pip install symbolic-compartmental-model.
• The package documentation can be found on ReadTheDocs.
• For all newcommers using the package for the first time, we recommend reading the Tutorial.
• If you want to learn more about the theoretical aspects of Compartmental Models, try reading: A quick guide to Compartmental Models
• For quick reference, you can see a list of the existing methods here: List of methods.

Examples using Binder

• Fitting predefined Compartmental Models to your data: