Notebook to fit the model described in Roehrl et al, Biochemistry 43.51 (2004): 16056-16066 to experimental data.
We use conda to set up a specific Python environment containing all the packages we want to use.
- Download this repository (either by using
git clone https://github.com/nobias-fht/competitive_binding.git
on the terminal or just downloading and unzipping). - If you don't have
conda
, install miniconda - In the command line terminal, navigate to the repository and type
conda env create -f env.yml
- Activate environment:
conda activate protprot
- Finally, start jupyter notebook by typing
jupyter notebook
and use the notebook.
The notebook expects the following format. for the .csv
file:
L_T (uM) | C1 replicate 1 (%) | ... | C2 replicate 1 (%) | ... |
---|---|---|---|---|
0.01 | 56.23 | ... | ... | ... |
0.1 | ... | ... | ... | ... |
10 | ... | ... | ... | ... |
The values should be separated by a comma (,
) and the decimals indicated by a dot (.
). Check out the example file.