kgo

Code and data for a knowledge graph and ontologies paper.

https://github.com/acil-group/kgo

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 7 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.0%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Code and data for a knowledge graph and ontologies paper.

Basic Info
  • Host: GitHub
  • Owner: ACIL-Group
  • License: cc0-1.0
  • Language: Python
  • Default Branch: main
  • Size: 411 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 4
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

KGO

Kowledge Graphs and Ontologies: code and data for the paper Transformation of Biomedical Data into Knowledge Graphs and Ontologies.

| Zenodo DOI | Test Status | Coverage | |:--------------:|:---------------:|:------------:| | DOI | Build Status | Codecov |

Table of Contents

Summary

This project implements a method of transforming biomedical gene-phenotype data into knowledge graphs and corresponding ontologies. This is demonstrated with a single data -> script -> output workflow.

The project is laid out as follows:

  • src/main_dystonia_graph_and_ontology_method.py: the main Python file running the experiment.
  • data/: the data files necessary to run the experiment.
  • out/: the destination for the generated files from the experiment.
  • example_output/: example files demonstrating the output of the experiment.

Usage

This project contains a main Python script that processes biomedical gene-phenotype dystonia data and outputs graph files of various kinds. This follows the pattern of creating a virtual Python environment, installing dependencies, running the main file, and exploring the output files. Brief installation instructions can be found in Setup, and use of the scripts can be found in Execution.

Setup

Create and activate a virtual Python environment with your favorite tool (e.g., conda, mamba, or venv).

For example, with conda:

shell conda create -n kgo python=3.11 conda activate kgo

Next, install dependencies while inside this virtual environment via the requirements.txt file at the top of this repo:

shell pip install -r requirements.txt

Execution

The entire experiment lives in a file called src/main_dystonia_graph_and_ontology_method.py. To execute it, simply run the file through the Python interpreter while in your virtual environment as follows:

shell python src/main_dystonia_graph_and_ontology_method.py

Three files are generated and saved to the out/ directory. Examples of the files that should be generated can be seen in the example_output/ directory.

Citation

This project has a citation file file that generates citation information for the repository, which can be accessed at the "Cite this repository button" under the "About" section of the GitHub page.

The latest archival of the project is also at https://doi.org/10.5281/zenodo.10463050, which has its own tools for generating citations according to your favorite citation style.

Owner

  • Name: Missouri S&T Applied Computational Intelligence Laboratory
  • Login: ACIL-Group
  • Kind: organization

Citation (CITATION.cff)

title: "ACIL-Group/KGO"
abstract: "A repository of code and data for the paper *Transformation of Biomedical Data into Knowledge Graphs and Ontologies*"
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
keywords:
  - "Knowledge Graphs"
  - "Ontologies"
  - "Graphs"
authors:
  - family-names: "Hier"
    given-names: "Daniel"
    orcid: https://orcid.org/0000-0002-6179-0793
    email: "hierd@mst.edu"
    alias: "dbhier"
    affiliation: "Missouri University of Science and Technology"
  - family-names: "Obafemi-Ajayi"
    given-names: "Tayo"
    orcid: https://orcid.org/0000-0002-0155-9733
    email: "tayoobafemiajayi@missouristate.edu"
    affiliation: "Missouri State University"
  - family-names: "Petrenko"
    given-names: "Sasha"
    orcid: https://orcid.org/0000-0003-2442-8901
    website: "https://ap6yc.github.io/"
    email: "sap625@mst.edu"
    alias: "AP6YC"
    affiliation: "Missouri University of Science and Technology"
  - family-names: "Wunsch"
    given-names: "Donald"
    name-suffix: "II"
    orcid: https://orcid.org/0000-0002-9726-9051
    email: "dwunsch@mst.edu"
    affiliation: "Missouri University of Science and Technology"

doi: 10.5281/zenodo.10463050
date-released: 2024-01-05
url: "https://doi.org/10.5281/zenodo.10463050"
repository-code: "https://github.com/ACIL-Group/KGO"
identifiers:
  - description: "The DOI of the latest KGO Zenodo archive."
    type: "doi"
    value: "10.5281/zenodo.10463050"

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Dependencies

requirements.txt pypi
  • matplotlib *
  • networkx *
  • pandas *
  • rdflib *
.github/workflows/Test.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
  • codecov/codecov-action v3 composite
tests/requirements.txt pypi
  • coverage * test
  • pytest-cov * test