bioactivity-prediction-app

Watch the tutorial video

Bioinformatics Project from Scratch - Drug Discovery #6 (Deploy Model as Web App) | Streamlit #22

Reproducing this web app

To recreate this web app on your own computer, do the following.

Create conda environment

Firstly, we will create a conda environment called bioactivity

conda create -n bioactivity python=3.7.9

Secondly, we will login to the bioactivity environement

conda activate bioactivity

Install prerequisite libraries

Download requirements.txt file

wget https://raw.githubusercontent.com/dataprofessor/bioactivity-prediction-app/main/requirements.txt

Pip install libraries

pip install -r requirements.txt

Download and unzip contents from GitHub repo

Download and unzip contents from https://github.com/dataprofessor/bioactivity-prediction-app/archive/main.zip

Generating the PKL file

The machine learning model used in this web app will firstly have to be generated by successfully running the included Jupyter notebook bioactivity_prediction_app.ipynb. Upon successfully running all code cells, a pickled model called acetylcholinesterase_model.pkl will be generated.

Launch the app

streamlit run app.py