Revise installation section in README.md

Updated Python version compatibility and improved wording in installation instructions.

Author: diegodoimo

README.md

@@ -147,12 +147,11 @@ overlap_x2 = no.return_label_overlap(k=10)
   > Allione et al., arXiv (2025)
 
 # Installation
-The package is compatible with the Python versions 3.8, 3.9, 3.10, 3.11, and 3.12.
-The methods of the classes ```DiffImbalance``` and ```CausalGraph``` are only compatible with Python>=3.9.
+The package is compatible with the Python versions 3.10, 3.11, 3.12, 3.13, and 3.14.
 We currently only support Unix-based systems, including Linux and macOS.
 For Windows machines, we suggest using the [Windows Subsystem for Linux (WSL)](https://en.wikipedia.org/wiki/Windows_Subsystem_for_Linux).
 
-The package requires `numpy`, `scipy`, `scikit-learn`, `jax`, `jaxlib` and `matplotlib` for the visualizations.
+The package requires `numpy`, `scipy`, `scikit-learn`, `jax`, `jaxlib`, and `matplotlib` for the visualizations.
 
 The package contains Cython-generated C extensions that are automatically compiled during installation. 
 
@@ -169,7 +168,7 @@ and install it with pip as follows:
 pip install git+https://github.com/sissa-data-science/DADApy
 ```
 
-Alternatively, if you'd like to modify the implementation of some function locally you can download the repository and install the package with:
+Alternatively, if you'd like to modify the implementation of some function locally, you can download the repository and install the package with:
 
 ```sh
 git clone https://github.com/sissa-data-science/DADApy.git
@@ -178,13 +177,13 @@ python setup.py build_ext --inplace
 pip install .
 ```
 
-The methods of the classes ```DiffImbalance``` and ```CausalGraph``` can be run on GPU, using a suitable installation of JAX on a GPU platform. The code has been tested using JAX v0.4.30 with CUDA 12, which can be installed with:
+The methods of the classes ```DiffImbalance``` and ```CausalGraph``` can be run on a GPU, using a suitable installation of JAX on a GPU platform. The code has been tested using JAX v0.4.30 with CUDA 12, which can be installed with:
 
 ```sh
 pip install --upgrade "jax[cuda12_pip]==0.4.30" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
 ```
 
-For more information on the installation of the JAX library on GPUs see the official [repository](https://github.com/google/jax?tab=readme-ov-file#installation).
+For more information on the installation of the JAX library on GPUs, see the official [repository](https://github.com/google/jax?tab=readme-ov-file#installation).
 
 
 # Citing DADApy