A suite of molecular simulation tools to cross-validate data from literature mining. Deployed as a flask app using multiple scientific Python libraries with cross-talk for materials informatics.
- Molecular property calculation
- Similarity comparison
- Reaction parsing and validation
- Molecule identification
- Property retrieval
- Drug-likeness analysis
- Molecular descriptor calculation
- Property visualization
- Structure rendering (2D/3D)
- Structure analysis
- Trajectory processing
- Property calculation
- Structure creation
- Geometry optimization
- Property analysis
- Structure creation (bulk, surface)
- Band structure calculation
- Property analysis
- Atomic orbital visualization
- Electron density plots
- Basis set selection
- Create conda environment:
conda env create -f environment.yml- Activate environment:
conda activate material-informatics- Install additional dependencies:
pip install -r requirements.txt- Pull the Docker image:
docker pull alanyahya/materialsinformatics:latest- Run the Docker container:
docker run -it --rm alanyahya/materialsinformatics:latest- Start the Flask application:
python app.py- Open web browser and navigate to:
http://localhost:5000
- Select analysis type from the available tabs
- Input required parameters
- View interactive results and visualizations
- Flask: Web framework
- Plotly: Interactive visualizations
- NumPy/SciPy: Scientific computing
- OpenBabel: Chemical toolbox
- ChEMBL API: Chemical database
- MDAnalysis: Molecular analysis
- ASE: Atomic simulations
- Pymatgen: Materials analysis
- RDKit: Cheminformatics
- scikit-learn: Machine learning
This project is licensed under the MIT License - see the LICENSE file for details.
- Start the Flask development server:
python app.pyAccess the dev deployment at http://localhost:5000
Access the prod deployment at http://localhost:8000