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Knowledge Graph importation that outputs MeTTa scripts using the [Biocypher](https://github.com/biocypher/biocypher) framework

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BioCypher MeTTa

A project for creating BioCypher-driven knowledge graphs and outputs MeTTa files.

⚙️ Installation (local)

  1. Clone this repository.
git clone https://github.com/Habush/biocypher-metta.git
  1. Install the dependencies using Poetry. (Or feel free to use your own dependency management system. We provide a pyproject.toml to define dependencies.)
poetry install
  1. You are ready to go!
poetry shell
python create_knowledge_graph.py

🛠 Usage

Structure

The project template is structured as follows:

.
│  # Project setup
│
├── LICENSE
├── README.md
├── pyproject.toml
│
│  # Docker setup
│
├── Dockerfile
├── docker
│   ├── biocypher_entrypoint_patch.sh
│   ├── create_table.sh
│   └── import.sh
├── docker-compose.yml
├── docker-variables.env
│
│  # Project pipeline
|── biocypher_metta
│   ├── adapters
│   ├── metta_writer.py
│
├── create_knowledge_graph.py
├── config
│   ├── biocypher_config.yaml
│   ├── biocypher_docker_config.yaml
│   └── schema_config.yaml

The main components of the BioCypher pipeline are the create_knowledge_graph.py, the configuration in the config directory, and the adapter module in the biocypher_metta directory. The input adapters are used for preprocessing biomedical databases and converting them into a BioCypher nodes and edges. The metta_writer.py script contains code to convert these BioCypher nodes and edges into MeTTa represntation.

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Knowledge Graph importation that outputs MeTTa scripts using the [Biocypher](https://github.com/biocypher/biocypher) framework

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  • Jupyter Notebook 94.9%
  • Python 5.1%