Revised documentation

.readthedocs.yaml

@@ -0,0 +1,24 @@
+# .readthedocs.yaml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Set the version of Python and other tools you might need
+build:
+  os: ubuntu-lts-latest
+  tools:
+    python: "3.10"
+
+# Build documentation in the docs/ directory with Sphinx
+sphinx:
+   configuration: docs/source/conf.py
+
+# Optionally declare the Python requirements required to build your docs
+python:
+   install:
+   - method: pip
+     path: .
+     extra_requirements:
+       - docs

README.md

@@ -1,36 +1,35 @@
-![Generic badge](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9-blue)
+![Generic badge](<https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9-blue>)
 ![Tests](https://github.com/Toepfer-Lab/model_duplication/actions/workflows/test.yml/badge.svg)
 ![GitHub last commit](https://img.shields.io/github/last-commit/Toepfer-Lab/model_duplication)
 ![GitHub pull requests](https://img.shields.io/github/issues-pr/Toepfer-Lab/model_duplication)
 
-A Python package that extends the COBRApy package with functions to represent time periods and organs by copying the
-original model for every organ time combination, which we refer to as phases. This way, different time ranges and
-customizable volumes of organs can be defined. Furthermore, a new model can be created automatically based on the
-specified organs and time periods for the simulation.
+Cobra2D is a Python package that extends COBRApy to automatically reconstruct time-resolved and/or multi-subsystem metabolic models. It generates context-specific submodels, adds linker and/or transfer reactions to connect them, and scales reactions to account for the lengths of the respective time intervals and the sizes of the subsystems. Cobra2D also provides a time interval- and subsystem size-aware weighted pFBA function.
 
 ### General process:
-* Define time ranges and organs
-* Individualization of single Phases
-    * Volume adjustment
-    * Time frame adjustments
-    * Defining linkers
-    * Adding special constraints for individual phases
-* Creation of a new model containing all phases with their associated constraints
+
+* Define time intervals (phases) and subsystems (e.g. cell types, tissues or organs)
+* Contextualizing sub-models
+  * Adjusting compartment sizes
+  * Adjusting time intervals
+  * Defining linker reactions (auxiliary reactions that connect phases and allow storage metabolites to be transferred across consecutive phases)
+  * Defining transfer reactions (auxiliary reactions that connect subsystems and allow exchange metabolites to be transferred across subsystems)
+  * Adding context-specific constraints to submodels
+* Construction of a new model containing all context-specific submodels and  their respective constraints
 
 For this process, this package provides functionalities to not only simplify this process, but also to easily save and
 share the defined settings with other people.
 
-### Possible usage of this package
+### Use cases for this package
 
-There are two ways to use this package. Either you use the functions implemented in Python to define phases and
-constraints or you create an XML file that can be read in and used to create a new model.
+There are two ways to use this package: functions implemented in Python can be used to define phases and constraints directly, or an XML file can be created and read in to generate a new model.
 
 ### Examples
-Examples of the use of this package can be found in the examples folder. There are examples that demonstrate the
-functions but also an XML file that shows how the parameters are stored.
+
+Examples of package usage can be found in the examples folder, including scripts that demonstrate the core functions and a sample XML file showing how parameters are stored. 
 
 ### Visualization
-The package also provides the possibility to get an overview of the created settings with the help of an animated or unanimated graphic.
+
+The package also provides the possibility to obtain an overview of the created settings via an animated or static graphic.
 
 <object data="../../assets/media/ConInteractive.gif" type="image/gif">
       <object data="https://github.com/Toepfer-Lab/model_duplication/blob/c42dfdac52524a93323e78e1f3d996aef5e01714/assets/media/ConInteractive.gif" type="image/gif">
@@ -39,8 +38,9 @@ The package also provides the possibility to get an overview of the created sett
 </object>
 
 ### Installation
-After cloning the repository, the package can be installed in the current Python environment using pip.
-So, in a terminal, the package can be installed with the following commands.
+
+After cloning the repository, the package can be installed in the current Python environment using pip. In a terminal, this can be done with the following commands: 
+
 ```
 git clone https://github.com/Toepfer-Lab/model_duplication